Shrestha Dash is passionate about uncovering actionable insights and exploring the ever-evolving landscape of technology and digital transformation. With a strong analytical foundation, she delves into topics such as ERP, enterprise software, and digital ecosystems, offering in-depth research and thoughtful analysis. Currently working as an Industry Research Analyst at ElevatIQ, she combines her expertise in research with a flair for storytelling, helping businesses navigate complex industry trends and make informed decisions.
Databricks has announced a series of new features particularly aimed at streamlining the development and governance of generative AI applications and agents. These updates are designed to enhance enterprise AI adoption by providing tools for model governance, batch inference, AI-driven analytics, and also evaluation frameworks. Therefore, by simplifying the AI deployment process, Databricks aims to reduce costs, increase accessibility, and improve compliance for enterprises utilizing large language models (LLMs).
This blog provides a detailed breakdown of Databricks‘ new updates, their implications, and also a broader analysis of the trends shaping enterprise AI adoption
Breakdown of Databricks New Updates
Centralized Governance with Mosaic AI Gateway
One of the key elements of Databricks’ new updates is the Mosaic AI Gateway, which particularly provides enterprises with a unified platform for governing LLMs.
Features and Benefits:
Ensures security, compliance, and access control for both open and closed-source AI models.
Streamlines licensing costs by preventing model duplication.
Allows companies to monitor model behavior, addressing concerns such as bias, drift, and regulatory compliance.
Provides an interface for legal, compliance, and security teams to approve AI models efficiently.
With this feature currently in public preview, enterprises can expect improved AI model governance and reduced risks associated with unregulated deployments.
Provision-Less Batch Inference
Another major enhancement in Databricks’ new updates is provision-less batch inference, which simplifies the process of running inference at scale.
Reduces costs by charging enterprises only for resources consumed.
Makes AI more accessible to data analysts without requiring MLOps expertise.
Use Cases:
Customer Support Analysis: Detecting trends in support tickets using AI.
E-commerce Optimization: Enriching product catalogs with AI-generated descriptions.
Compliance Audits: Running periodic risk assessments for financial institutions.
Customer Retention: Scoring customer databases for churn prediction.
Currently in public preview, this update is expected to benefit businesses seeking cost-effective AI scalability.
Enhanced Agent Evaluation Review App
AI agents play a crucial role in automating workflows, but ensuring their accuracy remains a challenge. To address this, Databricks’ new updates include an improved agent evaluation review app.
Key Enhancements:
Allows domain experts to review AI outputs and submit traces for labeling.
Supports the creation of custom evaluation criteria, eliminating reliance on spreadsheets and custom-built tools.
Enhances AI performance through structured feedback collection and iterative refinement.
With this feature, enterprises can enhance AI agent accuracy while maintaining transparency in evaluation.
AI/BI Genie Conversation API Suite
Databricks’ new updates also introduce the AI/BI Genie Conversation API Suite, a no-code tool designed for natural language-based data analysis.
Features:
Allows users to query datasets using natural language.
Automatically generates data visualizations for easy interpretation.
Enables developers to embed chatbot-based data analysis into platforms like Microsoft Teams, SharePoint, and Slack.
Supports context-aware follow-up queries, maintaining continuity in conversations.
Benefits:
Democratizes access to data insights, removing technical barriers such as SQL expertise.
Helps business users make data-driven decisions without requiring advanced analytics skills.
This update, also in public preview, could drive broader AI adoption in enterprise analytics.
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Databricks’ new updates align with a broader industry trend of streamlining AI adoption. Enterprises are increasingly looking for ways to govern AI models, reduce operational costs, and integrate AI-driven insights without requiring deep technical expertise.
Future Predictions
Increased AI Governance Adoption: As AI regulations tighten, platforms offering robust compliance features, like Mosaic AI Gateway, will gain traction.
Rise of Low-Code AI Development: Tools like AI/BI Genie Conversation API Suite indicate a shift toward no-code and low-code AI analytics, making data-driven decision-making more accessible.
Scalability in AI Deployment: Provision-less batch inference will likely encourage more companies to scale their AI implementations without heavy infrastructure investments.
Impact on Stakeholders
Enterprises: Will benefit from reduced operational overhead and better AI compliance.
Data Analysts: Can leverage batch inference and AI chat tools without requiring extensive coding skills.
Developers: Gain the ability to integrate AI functionalities seamlessly into existing applications.
Regulatory Bodies: May push for wider adoption of governance-focused solutions like Mosaic AI Gateway.
Model Reliability Issues: While Databricks’ new updates provide evaluation tools, ensuring AI outputs remain accurate across different use cases will be an ongoing challenge.
Cost Considerations: While provision-less batch inference optimizes spending, companies must still evaluate AI deployment costs against business value.
FAQs
How does the Mosaic AI Gateway improve AI governance for enterprises?
The Mosaic AI Gateway centralizes governance for both open and closed-source AI models, ensuring security, compliance, and access control. It prevents model duplication, reduces licensing costs, and provides monitoring tools to detect issues like bias, drift, and regulatory risks. This allows legal, compliance, and security teams to efficiently review and approve AI models, reducing risks associated with unregulated AI deployments.
What are the key benefits of provision-less batch inference for businesses?
Provision-less batch inference eliminates the need for complex infrastructure setup, allowing enterprises to run AI-powered analytics using simple SQL queries. This approach lowers costs by charging only for the resources consumed and makes AI more accessible to non-technical users like data analysts. Common use cases include customer support trend analysis, compliance audits, churn prediction, and e-commerce content optimization.
How does the AI/BI Genie Conversation API Suite enhance data accessibility?
The AI/BI Genie Conversation API Suite enables users to interact with datasets using natural language, automatically generating visual reports without requiring SQL or coding expertise. This feature allows enterprises to embed AI-powered data analysis into platforms like Microsoft Teams, Slack, and SharePoint, making insights more accessible to business users and enabling data-driven decision-making without technical barriers.
Boomi, a leader in integration and automation solutions, has launched Boomi AI Studio, a platform designed to help organizations manage, govern, and orchestrate AI agents at scale. This launch comes at a time when AI adoption is accelerating, and businesses are seeking structured solutions to monitor and optimize AI-driven processes. The platform provides a centralized system for managing AI agents, ensuring compliance, security, and efficiency across enterprise operations.
Boomi AI Studio introduces several key features, including AI agent design, governance, and control, as well as integrations with third-party AI providers. The platform is positioned to fill a gap in the market, where organizations struggle with fragmented AI ecosystems and regulatory challenges. Let’s take a closer look at what it offers, its potential impact on the industry, and key trends driving this innovation.
Key Features And Functionalities Of Boomi AI Studio
Boomi AI Studio provides a seamlessly integrated platform for AI agent creation, management, and coordination, featuring:
Agent Designer
Enables businesses to create and deploy AI agents with an intuitive no-code interface.
Ensures AI agents are grounded in enterprise data while maintaining security guardrails.
Control Tower
Provides real-time monitoring and governance for AI agents.
Helps mitigate security risks and ensure regulatory compliance.
Agent Garden
A personal workspace where users can interact with AI agents using natural language.
Supports AI agent development, testing, deployment, and continuous optimization.
Agent Marketplace
Allows organizations to access and customize AI agents from Boomi AI Studio and its AI ecosystem partners.
Hosted within Boomi Marketplace (formerly Boomi Discover).
Industry Perspectives On Boomi AI Studio
Boomi AI Studio has garnered attention from industry experts who recognize the platform’s potential to standardize AI agent management. Shawn Rogers, CEO of BARC US, noted that Boomi is “addressing a critical gap in the market, setting a standard for managing AI agents at scale.” He highlighted that while many vendors focus on releasing new AI agents, few provide robust solutions for managing, deploying, curating, and optimizing these environments effectively.
Amit Sinha, President & Co-Founder of WorkSpan, emphasized the significance of AI governance, stating that Boomi AI Studio delivers “comprehensive governance, seamless orchestration, and a robust framework for integrating AI across operations.” He added that the platform allows businesses to deploy AI agents with confidence, ensuring compliance and operational excellence.
Comparing Boomi AI Studio with Recent Industry Trends
The launch of Boomi AI Studio reflects a broader industry movement towards integrating advanced AI capabilities into enterprise solutions. This trend is evident in several recent developments across the technology sector:
ThoughtSpot’s Analyst Studio
ThoughtSpot unveiled its Analyst Studio, aiming to democratize data analytics by enabling users to create and share data-driven insights. This platform emphasizes user-friendly interfaces and real-time data processing, aligning with Boomi AI Studio’s focus on intuitive AI agent design and management. Both platforms prioritize empowering users with accessible tools to harness complex technologies.
SAP’s Business Data Cloud
SAP introduced the Business Data Cloud in partnership with Databricks, focusing on unified data environments to enhance decision-making processes. This initiative underscores the importance of seamless data integration and governance, principles central to Boomi AI Studio’s design. Both solutions address the need for cohesive data strategies to support AI functionalities and enterprise operations.
Zoho’s Analyst Day 2025 Announcements
During Zoho’s Analyst Day 2025, the company emphasized its commitment to AI-driven enterprise solutions, highlighting the integration of AI across its product suite. This mirrors Boomi’s approach with Boomi AI Studio, focusing on comprehensive AI agent management and orchestration. Both companies recognize the critical role of AI in enhancing business processes and the necessity for platforms that facilitate effective AI integration.
Contrasting Approaches
While Boomi AI Studio and the aforementioned platforms share a common goal of integrating AI and data solutions into business operations, their approaches differ:
Boomi AI Studio centers on AI agent management, providing tools for designing, governing, and orchestrating AI agents within a unified platform.
ThoughtSpot’s Analyst Studio focuses on democratizing data analytics, enabling users to generate insights without deep technical expertise.
SAP’s Business Data Cloud emphasizes creating unified data environments to support comprehensive analytics and decision-making processes.
Zoho’s AI Initiatives highlight the integration of AI across various applications to enhance overall enterprise functionality.
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Shift Towards Vendor-Agnostic AI Platforms – Many enterprises use AI solutions from multiple providers. A vendor-agnostic platform like Boomi AI Studio simplifies integration and management, reducing operational bottlenecks.
Rise of Agentic AI – Organizations are increasingly relying on AI agents to automate workflows. However, without a structured management system, AI-driven operations can become disorganized and inefficient. Boomi AI Studio addresses this need by offering a centralized platform for AI governance.
Growing Demand for AI Governance – Businesses require centralized AI monitoring to ensure security, compliance, and seamless enterprise integration. AI governance is becoming a top priority for organizations deploying multiple AI models, and Boomi AI Studio provides a structured approach to achieving this.
Impact on Key Stakeholders
Enterprises & AI-Driven Businesses – A cost-effective solution for managing and optimizing AI agents at scale. Also, reduces fragmentation in AI deployment, ensuring seamless cross-functional operations.
IT & Security Teams – Enhanced control and real-time visibility over AI agents. Stronger compliance frameworks will reduce regulatory risks.
Boomi’s AI Ecosystem Partners – Opportunity to expand AI capabilities by integrating their models into Boomi AI Studio’s marketplace. It is a structured approach to AI collaboration and interoperability.
Potential Challenges To Look Out For
Ethical AI & Bias Mitigation – Even with governance controls, ensuring AI agents operate fairly and without bias remains a challenge. Organizations must actively monitor AI behaviors, as biases in training data could lead to unintended and potentially harmful decision-making.
AI Agent Accountability & Transparency – As AI agents gain more autonomy in enterprise workflows, businesses must ensure transparency in their decision-making processes. This is especially critical in regulated industries, where tracking, auditing, and explaining AI-driven actions is a legal requirement.
Cybersecurity Risks & AI Exploits – AI-powered systems are attractive targets for cyber threats. Attackers may attempt to manipulate AI agents, introduce adversarial data, or also exploit automation vulnerabilities. While Boomi AI Studio includes security guardrails, businesses must remain proactive against emerging AI security risks.
Managing AI Agent Lifecycle & Evolution – AI agents require continuous updates, retraining, and version control. Without structured lifecycle management, outdated AI agents may provide inaccurate or inefficient results. While it offers governance tools, organizations must implement long-term AI maintenance strategies.
FAQs
What is Boomi AI Studio, and how does it benefit enterprises?
Boomi AI Studio is a platform designed to help businesses manage, govern, and orchestrate AI agents at scale. It provides a centralized system for designing, monitoring, and optimizing AI-driven processes while ensuring compliance and security. Enterprises benefit from reduced AI fragmentation, improved operational efficiency, and seamless integration with third-party AI providers.
How does Boomi AI Studio ensure AI governance and compliance?
Boomi AI Studio includes an Agent Control Tower, which enables real-time monitoring, governance, and security management for AI agents. It helps mitigate risks by enforcing compliance standards, tracking AI agent performance, and integrating with regulatory frameworks. This ensures businesses can deploy AI responsibly and maintain transparency in AI-driven decision-making.
Can Boomi AI Studio integrate with third-party AI solutions?
Yes, Boomi AI Studio is a vendor-agnostic platform, meaning it can integrate with third-party AI providers, starting with Amazon Bedrock. This flexibility allows organizations to use AI agents from different vendors while maintaining centralized control, reducing operational silos, and enhancing AI ecosystem collaboration.
Zoho Corporation has introduced Zoho Projects Plus, a new project management platform designed for mid-sized and enterprise organizations. This launch aims to provide businesses with a unified, AI-driven solution that combines multiple project management functionalities in one ecosystem. With the integration of Zoho Projects Plus, WorkDrive, Analytics, and Sprints, the platform supports both Agile and Waterfall methodologies, making it adaptable to diverse project management needs.
This launch comes at a time when companies are increasingly prioritizing AI-powered insights, data-driven decision-making, and cross-team collaboration to streamline operations. Let’s take a closer look at what Zoho Projects Plus offers, its potential impact on the industry, and key trends driving this innovation.
Breakdown of Zoho Projects Plus
In this section, we will explore the key components of Zoho Projects Plus and how they contribute to a more efficient and streamlined project management experience. With businesses increasingly relying on AI-driven insights, unified platforms, and flexible workflows, understanding the features of Zoho Projects Plus is essential for organizations looking to enhance collaboration, optimize resources, and improve decision-making.
Unified Project Management Ecosystem
One of the most significant aspects of Zoho Projects Plus is its integration of four Zoho applications:
Zoho Projects – Task tracking, milestone planning, and collaboration tools.
Zoho WorkDrive – A secure, cloud-based file storage and document-sharing solution.
Zoho Analytics – Advanced data analytics and real-time reporting dashboards.
By bringing these applications under a single platform, Zoho Projects Plus aims to reduce fragmentation in project management and improve cross-functional collaboration for enterprises.
AI-Driven Insights for Smarter Decision-Making
As AI adoption grows in the enterprise sector, tools like Zoho Projects Plus are expected to help organizations proactively manage risks and optimize resources, leading to better project outcomes. Zoho Projects Plus incorporates Zoho’s AI engine, Zia, to enhance efficiency through:
Predictive analytics – Forecasting project risks and delays.
Resource optimization – Smart workload distribution to avoid bottlenecks.
Automated reporting – AI-generated insights for tracking performance.
Hybrid Project Management: Agile + Waterfall
Unlike traditional project management platforms that focus on either Agile or Waterfall, Zoho Projects Plus supports both methodologies. This dual approach ensures businesses can choose the workflow that best fits their project needs, whether it’s structured milestone-based planning (Waterfall) or flexible iterative development (Agile). For companies that operate in fast-moving environments, such as software development, marketing, or product innovation, this flexibility can lead to improved adaptability and execution.
Data-Driven Decision Making
As data-driven decision-making becomes increasingly important for businesses, having an integrated analytics tool within Zoho Projects Plus provides a strategic advantage. With Zoho Analytics integrated into Zoho Projects Plus, businesses gain access to:
Bottleneck identification – Highlighting areas that require immediate attention.
Real-time dashboards – Tracking project progress and KPIs.
Advanced reporting tools – Customizable reports for insights into productivity, financials, and resource allocation.
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With these factors, Zoho Projects Plus positions itself as a strong competitor in the project management software space, challenging established players like Asana, Monday.com, and Trello.
Zoho Projects has seen a 20% year-over-year revenue growth in 2024.
A significant number of businesses are migrating from Microsoft Projects and JIRA to Zoho Projects Plus.
Zoho aims to offer cost-effective project management with a 27% lower pricing model than purchasing the included applications separately.
Analyst’s Take: Industry Trends, Predictions & Challenges
In this section, we will explore the key industry trends driving the adoption of AI-powered project management, future predictions for the evolving market, and the potential impact on stakeholders. Additionally, we will examine the challenges organizations may face when adopting new technologies.
Industry Trends Observed
Rise of AI in Project Management – More businesses are integrating AI-driven insights to automate workflow management.
Growing Demand for Hybrid Methodologies – Companies are moving away from rigid structures, opting for a mix of Agile and Waterfall approaches.
Increased AI-driven Project Automation – Expect more automated task prioritization and resource allocation capabilities in the future.
Expansion into Industry-Specific Solutions – Zoho may introduce industry – tailored versions of Zoho Projects Plus for healthcare, manufacturing, and finance.
More Competition from Enterprise Software Giants – Microsoft, Salesforce, and SAP may introduce AI-driven enhancements to their project management tools in response.
Project Managers & Teams – Improved collaboration, predictive insights, and streamlined workflows.
Zoho Customers – Seamless transition for existing Zoho users, integrating their workflow into Zoho Projects Plus.
Challenges & Considerations
Integration Complexity – Businesses migrating from non-Zoho platforms may face a learning curve and data migration challenges.
Market Adoption Rate – While the pricing model is competitive, customer acquisition from established platforms like Microsoft Projects and JIRA may take time.
Regulatory & Security Compliance – As businesses move toward AI-enhanced project management, ensuring data privacy and compliance will be crucial.
FAQs
How does Zoho Projects Plus differ from other project management platforms?
Zoho Projects Plus stands out by offering a unified ecosystem that integrates Zoho Projects, Zoho WorkDrive, Zoho Analytics, and Zoho Sprints. This combination provides businesses with AI-driven insights, seamless cross-functional collaboration, and support for both Agile and Waterfall methodologies—all within a single platform. Additionally, it offers cost savings by bundling these tools at a 27% lower price than purchasing them separately.
What AI capabilities does Zoho Projects Plus offer?
Zoho Projects Plus incorporates Zoho’s AI engine, Zia, to enhance project management through predictive analytics, automated reporting, and resource optimization. It helps forecast project risks, identify bottlenecks, and suggest workload distribution strategies, enabling smarter decision-making and improved project outcomes.
Is Zoho Projects Plus suitable for businesses using both Agile and Waterfall methodologies?
Yes, Zoho Projects Plus is designed to support both Agile and Waterfall methodologies, making it adaptable to different project needs. Teams can choose structured milestone-based planning (Waterfall) or flexible iterative development (Agile), ensuring that businesses in various industries, such as software development, marketing, and product innovation, can effectively manage projects.
ServiceNow has made a bold move in the AI-driven enterprise automation space with its latest acquisition of Moveworks for $2.85 billion. This deal, a mix of cash and stock, is the largest in ServiceNow’s history. It signals the intent to expand deeper into AI and CRM. Moveworks, known for its AI-powered enterprise assistant technology, brings strong capabilities in automation and enterprise search. Thus, making it a valuable addition to ServiceNow’s ecosystem.
With AI rapidly shaping the future of business operations, this acquisition is expected to enhance ServiceNow’s offerings. Also, helping enterprises streamline workflows and improve digital employee experiences. Let’s take a closer look at what this means for the industry, customers, and ServiceNow’s long-term growth strategy.
The Breakdown Of The ServiceNow Moveworks Acquisition
In the breakdown of the ServiceNow Moveworks acquisition, we will explore the key elements of this $2.85 billion deal. This includes its financial structure and expected timeline for completion. We will examine how Moveworks’ AI-powered enterprise assistant enhances ServiceNow’s automation and workflow solutions. Thus, strengthening its position in the enterprise software market. Lastly, we will also discuss why ServiceNow is prioritizing AI and CRM investments.
The Financials and Deal Structure
Valued at $2.85 billion, the ServiceNow Moveworks acquisition will be finalized through a combination of cash and stock. The deal is expected to close in the second half of 2025, pending regulatory approvals and other standard conditions. This acquisition marks a significant milestone for ServiceNow. Thus, intensifies its AI investments to stay ahead in an increasingly competitive market.
What Moveworks Brings to the Table
Moveworks has built a strong reputation in the AI space with its conversational enterprise assistant. Also, it integrates seamlessly into business applications. The platform allows employees to get instant support, automate routine tasks, and access company-wide information effortlessly. It has more than 350 enterprise clients, including Siemens, Unilever, Toyota, and Instacart. Hence, Moveworks has established itself as a leader in AI-powered automation.
Through the ServiceNow Moveworks acquisition, ServiceNow gains access to this cutting-edge AI technology. It also gains access to a team of 500 AI experts who will be joining its ranks. This move strengthens ServiceNow’s AI capabilities and accelerates its goal of delivering autonomous AI-driven business solutions.
Why ServiceNow is Investing in AI and CRM
The ServiceNow Moveworks acquisition is part of a broader trend where companies are integrating AI into their operations to drive efficiency. By incorporating Moveworks’ AI assistant, ServiceNow aims to enhance its CRM capabilities, providing customers with a more seamless “sell, fulfil, and service” experience.
More importantly, this acquisition aligns with ServiceNow’s long-term vision of AI-powered automation, particularly in the growing area of agentic AI – AI systems that can autonomously complete business processes with minimal human intervention. This development could redefine how enterprises handle customer service, HR, IT support, and other critical functions.
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Analyst’s Take On The ServiceNow Moveworks Acquisition
How This Acquisition Fits Into Industry Trends
The AI-driven automation space has seen significant consolidation recently, with major players like Microsoft, Salesforce, and Oracle making aggressive AI investments. The ServiceNow Moveworks acquisition is a direct response to these market shifts, ensuring that ServiceNow remains competitive in an industry increasingly dominated by AI-driven solutions.
What Lies Ahead for ServiceNow and Its Customers
Enhanced AI Capabilities: With Moveworks’ AI assistant technology integrated into its platform, ServiceNow is expected to roll out more advanced automation solutions that simplify enterprise workflows.
Stronger Competitive Position: The ServiceNow Moveworks acquisition places ServiceNow in direct competition with other enterprise software giants focused on AI-powered CRM and automation.
Increased AI Adoption Among Businesses: As AI becomes more embedded in enterprise systems, companies using ServiceNow may benefit from smarter self-service tools, improved automation, and better operational efficiency.
Potential Impact on Stakeholders
ServiceNow’s Existing Customers: Organizations already using ServiceNow’s platform could see improved AI-powered automation features, particularly in service management and workflow optimization.
Moveworks’ Customers: While Moveworks’ existing clients stand to gain from deeper AI integration within the ServiceNow platform, they may also face changes in service models, pricing structures, or platform migration requirements.
ServiceNow’s Workforce and AI Talent Pool: With 500 AI specialists joining ServiceNow from Moveworks, the company is expected to strengthen its research and development efforts, fueling future AI advancements.
Challenges and Considerations
While the ServiceNow Moveworks acquisition presents significant opportunities, there are a few hurdles to consider:
Integration Complexity: Bringing Moveworks’ AI assistant into ServiceNow’s existing ecosystem will require careful execution to ensure compatibility and maintain a seamless user experience.
Market Reactions: Following the acquisition announcement, ServiceNow’s stock saw a temporary dip of 5.5%, reflecting some investor uncertainty about the financial impact of this large-scale AI investment.
Regulatory Approval: As with any major acquisition, regulatory scrutiny could delay the finalization of the deal or introduce unforeseen compliance challenges.
FAQs
What does the Moveworks acquisition mean for ServiceNow’s AI capabilities?
The ServiceNow Moveworks acquisition strengthens ServiceNow’s AI-driven automation by integrating Moveworks’ conversational AI assistant into its platform. This will enhance workflow automation, enterprise search, and self-service capabilities, allowing businesses to streamline operations and improve digital employee experiences.
How will this acquisition impact Moveworks’ existing customers?
Moveworks’ clients will likely benefit from deeper AI integration within the ServiceNow ecosystem, potentially gaining access to more advanced automation tools. However, they may also experience changes in pricing structures, service models, or platform migration requirements as the integration progresses.
When will the acquisition be finalized, and what challenges might arise?
The ServiceNow Moveworks acquisition is expected to close in the second half of 2025, pending regulatory approvals and other standard conditions. Challenges may include integration complexities, regulatory scrutiny, and initial market fluctuations, as seen with ServiceNow’s stock experiencing a temporary decline after the announcement.
Zendesk, a leader in AI-driven customer service solutions, recently announced its agreement to acquire Local Measure, an Australian-based Contact Center as a Service (CCaaS) provider. This Zendesk acquisition is aimed at expanding its AI-powered voice capabilities and deepening its integration with Amazon Connect, AWS’s cloud-based contact center solution. The move signifies Zendesk’s commitment to enhancing its position in the enterprise customer service market, especially in high-volume, complex service environments.
The Zendesk acquisition of Local Measure aligns with the broader industry trend of consolidating AI-driven customer experience platforms. As businesses increasingly shift towards cloud-based and AI-enhanced customer service operations, this deal could mark a significant milestone in redefining how companies approach customer interactions through voice technology. This article provides a detailed breakdown of the Zendesk Acquisition and an analysis of its potential impact on businesses, stakeholders, and the broader industry.
Breakdown of the Zendesk Acquisition
The Zendesk acquisition of Local Measure strengthens its AI-powered voice automation and deepens integration with Amazon Connect. This breakdown will explore the strategic intent behind the acquisition, its financial and legal aspects, and leadership perspectives.
Strategic Intent and Expansion into AI-Powered Voice Solutions
The Zendesk acquisition of Local Measure is a strategic move to strengthen its offerings in AI-powered voice automation. Local Measure specializes in enhancing customer interactions using AI-driven automation, intelligent call routing, and real-time insights. By acquiring this technology, Zendesk aims to provide a seamless, scalable, and intelligent voice solution for enterprises handling high customer volumes.
This acquisition will allow Zendesk to:
Provide businesses with enhanced customer service analytics and real-time decision-making tools.
Improve AI-driven automation and call routing.
Offer a fully integrated voice solution with Amazon Connect.
Strengthening AWS Integration with Amazon Connect
A key highlight of the Zendesk acquisition is the deeper integration with Amazon Web Services (AWS). Local Measure has been known for its seamless compatibility with Amazon Connect, a cloud-based contact center platform. The acquisition will likely boost Zendesk’s ability to offer cloud-native AI-powered voice solutions by leveraging AWS’s security, scalability, and automation features.
For Zendesk, this means:
A more robust partnership with AWS.
Better cloud-native capabilities for large enterprises.
Faster deployment of AI-driven customer support tools.
With AWS becoming a dominant player in the cloud contact center space, this Zendesk acquisition could position the company as a formidable alternative to traditional CCaaS providers.
The Financial and Legal Aspects of the Acquisition
The Zendesk acquisition of Local Measure is being executed under Australian corporate law through a scheme of arrangement. The deal, which is expected to close by May 2025, is subject to shareholder, regulatory, and court approvals. While exact financial details have not been disclosed, industry estimates suggest the deal values Local Measure at around $100 million.
The financial structure of the acquisition reflects Zendesk’s strategic investment in long-term growth rather than a short-term revenue boost. With AI-powered voice services gaining traction, this Zendesk acquisition could provide long-term competitive advantages, particularly in enterprise-level customer service markets.
Leadership Perspectives and Market Positioning
Zendesk’s leadership has emphasized that this Zendesk acquisition is a step toward providing a fully integrated AI-powered voice solution. CEO Tom Eggemeier stated, “With the acquisition of Local Measure, Zendesk is accelerating its ability to provide a fully integrated, AI-powered voice solution that combines the best of our platform with the flexibility, security, and scalability of Amazon Connect.”
From Local Measure’s perspective, CEO Jonathan Barouch remarked, “This acquisition means faster deployment, reduced complexity, and cloud-native innovation. Together with Zendesk, we are bringing a fresh alternative to legacy contact center providers.”
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The Zendesk acquisition of Local Measure reflects key industry trends, including the shift toward AI-powered customer service, cloud-based platforms, and market consolidation. This section will analyze how the acquisition aligns with these trends, its impact on various stakeholders, and potential challenges Zendesk may face in execution and adoption.
Industry Trends and Market Context
The Zendesk acquisition of Local Measure aligns with several key industry trends:
Shift to AI-powered Customer Service: Enterprises are increasingly investing in AI-driven voice solutions to enhance customer interactions.
Consolidation in the CCaaS Market: Major players are acquiring specialized companies to strengthen their AI and automation capabilities.
Impact on Stakeholders
The Zendesk acquisition is expected to affect various stakeholders in different ways:
Customers: Zendesk’s existing customers will likely benefit from a more comprehensive AI-powered voice solution. The integration with AWS could lead to improved scalability and security.
Competitors: CCaaS providers like Five9, Genesys, and NICE may face increased competition as Zendesk strengthens its AI-powered voice offerings.
Investors: If the integration succeeds Zendesk’s market position could strengthen, potentially leading to long-term stock growth.
Employees: Local Measure’s team will likely integrate with Zendesk’s AI and customer service divisions, contributing to product innovation.
Challenges and Potential Risks
While the Zendesk acquisition presents significant opportunities, there are potential challenges:
Integration Complexity: Merging AI-driven voice capabilities with Zendesk’s existing infrastructure could pose technical and operational challenges.
Regulatory Approvals: The acquisition must pass regulatory scrutiny in multiple jurisdictions, which could delay the timeline.
Competition from Other CCaaS Providers: Established CCaaS providers are also investing heavily in AI, which means Zendesk will need to differentiate itself in a crowded market.
Customer Adoption: While AI-driven voice solutions are growing, some enterprises may still be hesitant to transition from legacy systems.
FAQs
Why is Zendesk acquiring Local Measure?
The Zendesk acquisition of Local Measure is aimed at enhancing its AI-powered voice capabilities and deepening integration with Amazon Connect. This move aligns with the growing industry trend of AI-driven customer experience solutions, allowing Zendesk to offer enterprises a more scalable, intelligent, and cloud-native contact center platform
How will this acquisition impact Zendesk’s customers?
Zendesk’s customers will benefit from improved AI-driven voice automation, better call routing, and enhanced real-time analytics. The integration with AWS’s Amazon Connect will also provide greater scalability, security, and flexibility, making customer service operations more efficient.
What challenges might Zendesk face with this acquisition?
Potential challenges include technical complexities in integrating Local Measure’s AI capabilities with Zendesk’s platform, regulatory approvals across jurisdictions, and competition from established CCaaS providers like Five9 and Genesys. Additionally, customer adoption of AI-powered voice solutions may take time as businesses transition from legacy systems.
SAP has unveiled Joule AI Agents, an expansion of its generative AI copilot, Joule, aimed at transforming enterprise collaboration and automation. By integrating AI-driven agents across business functions like finance, sales, and customer service, SAP seeks to streamline processes, reduce inefficiencies, and enable faster decision-making. These AI agents leverage SAP Business Data Cloud and SAP Knowledge Graph to ensure accurate, context-driven actions. This article provides a detailed breakdown of SAP’s announcement, the key components of Joule AI Agents, and an analysis of its potential impact on businesses, stakeholders, and the broader industry.
Breakdown of SAP’s Joule AI Agents
Joule AI Agents are designed to streamline business operations by improving cross-functional collaboration and leveraging enterprise data effectively. With features like automated classification, knowledge management, and dispute resolution, Joule AI Agents enhance workflow efficiency across various departments.
One of the primary objectives of Joule AI Agents is to resolve inefficiencies in business workflows, where different departments operate in silos. Many organizations struggle with aligning data, decisions, and actions, leading to delays and miscommunications. Joule AI Agents aim to bridge these gaps, ensuring seamless coordination across business functions.
Foundation: SAP Business Data Cloud & SAP Knowledge Graph
SAP highlights that AI effectiveness depends on access to high-quality, unified data. The SAP Business Data Cloud serves as a centralized data layer, combining SAP and non-SAP sources to provide AI agents with relevant business context. Additionally, the SAP Knowledge Graph acts as a semantic bridge, helping Joule AI Agents understand relationships between data and processes. This allows the agents to make informed, context-aware decisions rather than relying solely on generic AI models.
Key AI Agents Introduced by SAP
SAP has launched ready-to-use Joule agents across multiple business functions, with further expansions planned in 2025. Some of the notable agents include:
Cash Collection Agent: Analyzes and resolves disputes in seconds by working across finance, customer service, and operations.
Q&A Agent: Proactively identifies customer questions and provides accurate answers based on internal knowledge bases.
Knowledge Creation Agent: Converts new case resolutions into structured knowledge articles, improving knowledge management.
Case Classification Agent: Intelligently classifies and routes customer inquiries, even when specific keywords are missing.
These AI agents work collaboratively, enabling end-to-end process automation. For example, the Case Classification Agent can detect a billing dispute and immediately assign it to the Cash Collection Agent, reducing resolution time.
Customization with Joule Studio
SAP plans to launch a custom agent builder within Joule Studio, allowing businesses to create AI agents tailored to their specific processes. This no-code/low-code tool will empower companies to design AI-driven workflows using SAP Build, ensuring adaptability to unique business needs.
AI Orchestration: Beyond a Copilot
SAP positions Joule not just as an AI assistant but as an AI orchestrator capable of managing multiple AI agents across different business areas. By coordinating out-of-the-box and custom AI agents, SAP aims to create a fully automated, adaptive AI ecosystem within enterprises.
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The introduction of Joule AI Agents aligns with the growing trend of AI-driven enterprise automation, positioning SAP alongside key industry players. As businesses integrate Joule AI Agents, factors like data security, AI adoption challenges, and evolving workforce roles will shape the long-term impact of this technology.
Industry Trends & Competitive Landscape
The rise of agentic AI, where AI systems autonomously complete complex, multi-step processes, is a growing trend. Competitors like Microsoft Copilot, Salesforce Einstein AI, and Google Duet AI are also moving towards AI-powered workflow automation.
SAP’s focus on trusted business data differentiates Joule from general-purpose AI assistants, as data governance and reliability are major concerns in enterprise AI adoption.
Future Predictions
SAP’s planned expansion of Joule AI Agents across its Business Suite suggests a long-term vision where AI becomes deeply embedded in ERP systems, potentially reducing human intervention in routine processes.
The introduction of a custom AI agent builder signals an upcoming trend where businesses will increasingly develop tailored AI solutions rather than relying on pre-built AI models.
Impact on Stakeholders
Enterprises: Organizations using SAP’s ERP solutions can expect faster decision-making, reduced manual effort, and enhanced process efficiency. However, they may need to invest in AI training and integration to maximize benefits.
Employees: While AI-driven automation can increase productivity, concerns over job displacement in areas like customer support and finance may arise. Instead of replacing roles, AI is likely to augment human workers by handling repetitive tasks.
SAP Partners & Developers: The Joule Studio AI agent builder presents opportunities for developers and SAP partners to create and monetize custom AI solutions.
Challenges & Considerations
Data Privacy & Security: As AI agents access sensitive business data, ensuring compliance with GDPR, CCPA, and enterprise security policies will be critical.
Integration Complexity: Businesses operating on hybrid IT infrastructures (SAP + non-SAP applications) may face challenges in achieving seamless AI integration.
User Adoption: Despite automation benefits, enterprise AI adoption often faces resistance due to concerns over AI reliability and trust. SAP may need to focus on AI explainability and user training.
FAQs
What are SAP Joule AI Agents, and how do they improve business processes?
SAP Joule AI Agents are AI-driven assistants designed to automate and optimize business workflows across various functions like finance, sales, and customer service. They leverage SAP Business Data Cloud and SAP Knowledge Graph to access relevant business data, enabling seamless collaboration, faster decision-making, and more efficient process execution.
How do Joule AI Agents ensure data accuracy and reliable decision-making?
Joule AI Agents rely on SAP Business Data Cloud to unify data from both SAP and non-SAP sources, ensuring AI models have access to accurate and context-driven information. Additionally, the SAP Knowledge Graph helps these AI agents understand data relationships, making their recommendations and actions more precise and relevant.
Can businesses customize Joule AI Agents to fit specific operational needs?
Yes, SAP plans to introduce Joule Studio, a tool that allows businesses to build custom AI agents tailored to their unique processes. This no-code/low-code platform will enable organizations to configure AI-driven workflows using SAP Build, ensuring greater adaptability and alignment with business requirements.
ThoughtSpot Analyst Studio, a new data preparation and analytics platform, has been launched to enhance efficiency for data teams. Designed to streamline workflows, it aims to address challenges such as slow time-to-value, data silos, high costs, and limited technical capabilities. By incorporating AI-assisted tools, the platform empowers analysts to optimize data readiness for AI and business intelligence.
As organizations increasingly depend on AI-driven insights, the demand for seamless, cost-effective data preparation has grown. ThoughtSpot Analyst Studio bridges the gap between raw data and actionable intelligence, offering tools to prepare AI-ready datasets, reduce costs, and improve accessibility. Below is a detailed breakdown of its features, target audience, technical aspects, and strategic implications.
Purpose and Benefits
Solving Key Challenges in Data Preparation
ThoughtSpot Analyst Studio is built to address several pain points for data teams and organizations:
Eliminating Data Silos: It integrates various sources into a unified workspace, ensuring seamless data access.
Reducing Analytics Costs: Features like Datasets allow users to choose between real-time or periodic data snapshots, optimizing cloud expenditure.
Enhancing AI Readiness: The AI-assisted SQL editor and real-time collaboration tools help analysts prepare structured datasets for AI applications.
Improved Collaboration: The platform fosters cross-functional teamwork between analysts, engineers, and business teams.
Optimized Cloud Resource Utilization: With configurable data extraction and live querying, organizations can balance performance and cost efficiency.
Key Features and Functionality
AI-Ready Data Preparation
ThoughtSpot Analyst Studio enables direct connectivity to multiple data sources, including cloud data warehouses, databases, and applications like Google Sheets.
The AI-assisted SQL editor includes autocomplete, query history tracking, and NLP-based query generation, making it faster and more accessible for users of all skill levels.
End-to-End Analytics Workflow
ThoughtSpot Analyst Studio combines ad-hoc analysis and advanced data science, eliminating the need for multiple tools.
Users can choose between live data connections and extracted datasets, helping them optimize cloud performance and costs.
Unique Features Compared to Other Data Preparation Tools
Seamless Multi-Language Support: The platform supports SQL, Python, and R within a single interface, eliminating the need for separate tools.
Datasets for Performance Optimization: The “Datasets” feature allows users to work with either static snapshots or real-time data feeds, ensuring efficient resource usage and cost control.
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Data Analysts: Gain access to AI-assisted SQL querying and seamless integration with major cloud platforms.
Business Teams: The platform enables real-time collaboration, reducing reliance on technical teams.
Enterprises and SMBs: While large enterprises may see the most impact, smaller businesses can also leverage its advanced tools for cost and performance optimization.
Compatibility with Cloud Platforms
The tool is designed to be user-friendly, with AI assistance making it accessible to both technical and non-technical users.
ThoughtSpot Analyst Studio integrates with leading data platforms like Snowflake, Databricks, and Google BigQuery.
Strategic Value and Industry Relevance
Industry Trends Driving the Launch
Self-service analytics is growing, increasing demand for user-friendly data tools.
AI-powered query generation and automated data preparation are becoming key differentiators in the analytics market.
Businesses are seeking cost-optimized cloud solutions as cloud computing expenses continue to rise.
Enhancing Collaboration Between Data and Business Teams
ThoughtSpot Analyst Studio supports multi-language data manipulation and real-time collaboration, thus ensuring smoother workflows.
The ability to perform ad-hoc analysis without needing additional tools particularly reduces dependency on IT and data engineers.
Future Developments and AI Expansion
Potential expansions could include automated data cleansing, predictive analytics, and also customizable AI models.
While no specific enhancements have been announced, ThoughtSpot’s investment in AI suggests further AI-driven features may be introduced.
Practical Details and Access
Availability and Pricing
For Existing ThoughtSpot Customers: ThoughtSpot Analyst Studio is available as an add-on for ThoughtSpot Cloud users.
Pricing: While exact pricing is not disclosed, interested users can contact ThoughtSpot for customized pricing based on their requirements.
Adoption Considerations
Learning Curve: While AI-assisted tools simplify workflows, organizations may require training to maximize usage.
Vendor Lock-in Risks: Businesses using Tableau or Power BI may face integration challenges when transitioning.
Cost-Benefit Analysis: Organizations should assess whether live vs. extracted datasets align with their budget and data usage needs.
Analyst’s Take: Key Considerations and Market Impact
Impact on Different Stakeholders
Data Analysts: Gain greater control over data preparation, thus reducing IT dependency.
Business Leaders: Improved data accessibility accelerates AI-driven decision-making.
Data Engineers: Workloads may shift as analysts take on more data transformation tasks.
Competitive Landscape
ThoughtSpot Analyst Studio vs. Tableau, Looker, and Power BI: The platform is positioned as a self-service, AI-powered alternative but will compete with established BI tools.
AI in Analytics: AI-assisted query generation and automation are likely to become industry standards, particularly making ThoughtSpot Analyst Studio increasingly relevant.
Long-Term Viability: Buyers should assess whether ThoughtSpot’s AI-driven approach aligns with their long-term analytics strategy.
FAQs
How does ThoughtSpot Analyst Studio improve data preparation for AI and analytics?
ThoughtSpot Analyst Studio streamlines data preparation by integrating AI-assisted tools that simplify SQL querying, automate data structuring, and enhance collaboration. It connects to multiple data sources, including cloud warehouses and applications like Google Sheets, ensuring seamless access. Additionally, features like real-time and extracted datasets allow businesses to optimize costs while maintaining AI-readiness.
Who can benefit the most from ThoughtSpot Analyst Studio?
ThoughtSpot Analyst Studio is designed for data analysts, business teams, and enterprises of all sizes. Analysts gain AI-powered SQL assistance, business users can collaborate in real-time without technical dependencies, and organizations benefit from cost-optimized cloud resource utilization. Both large enterprises with complex data needs and smaller businesses leveraging cloud analytics can take advantage of its flexible data preparation tools.
What makes ThoughtSpot Analyst Studio different from other data preparation tools?
Unlike traditional data preparation tools, ThoughtSpot Analyst Studio offers seamless multi-language support (SQL, Python, and R) within a single interface, eliminating the need for external platforms. Its AI-driven query generation, real-time collaboration, and Datasets feature provide greater flexibility by allowing users to choose between live connections and extracted snapshots, ensuring optimized performance and cost efficiency.
Blackstone and Vista Equity Partners have completed their Smartsheet acquisition, a work management and collaboration platform, in an $8.4 billion all-cash transaction. Smartsheet shareholders received $56.50 per share, a price reflecting an 8.5% premium over the company’s last closing price before the announcement and a 41% premium over its 90-day volume-weighted average stock price as of July 17, 2024. Following the completion of the deal, Smartsheet has officially transitioned into private ownership and has been delisted from the New York Stock Exchange.
The Smartsheet acquisition is part of a broader trend of private equity firms investing in high-growth SaaS companies, particularly those that integrate AI and automation into enterprise workflows. With Blackstone and Vista Equity Partners taking control, the focus will likely shift toward enhancing Smartsheet’s AI capabilities, expanding its market reach, and improving operational efficiency. This transition raises key questions about its impact on customers, employees, and the competitive landscape of the work management software industry.
Breakdown of the Smartsheet Acquisition
The Smartsheet acquisition agreement includes several key elements:
Transaction Value and Premium: The deal was completed at $56.50 per share, representing an 8.5% increase from Smartsheet’s last closing price before the announcement and a 41% premium over its 90-day volume-weighted average stock price as of July 17, 2024.
Go-Shop Period: The agreement allowed Smartsheet a 45-day “go-shop” period to explore alternative acquisition offers. However, no competing proposals emerged.
Delisting from NYSE: With the Smartsheet acquisition finalized, the company’s shares have been removed from public trading, making it a privately held firm.
This deal highlights the growing interest of private equity firms in the SaaS market, where recurring revenue models and AI-driven automation make companies like Smartsheet attractive investment opportunities.
Strategic Rationale for the Smartsheet Acquisition
Blackstone and Vista Equity Partners have been actively investing in enterprise SaaS platforms. Their investment in Smartsheet signals confidence in its potential for long-term growth and scalability. The Smartsheet acquisition is expected to enable the company to:
Enhance AI and Automation Capabilities: AI-driven automation is a key focus area in work management software. With additional investment, Smartsheet is likely to integrate more AI-powered features, such as predictive analytics and workflow automation.
Improve Operational Efficiencies: Private equity firms often streamline operations in acquired companies, which could lead to restructuring efforts aimed at enhancing profitability and cost management.
Expand Market Reach: Smartsheet may prioritize global expansion and deeper penetration into the enterprise sector.
These strategic priorities align with broader trends in SaaS, where automation and AI-driven solutions are becoming critical competitive differentiators.
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Impact of the Smartsheet Acquisition on Stakeholders
The acquisition of Smartsheet by Blackstone and Vista Equity Partners is expected to bring changes across multiple stakeholder groups, including customers, employees, and competitors. Here’s how each group may be impacted by this acquisition.
For Smartsheet Customers
Existing users of Smartsheet may see continued investment in AI-driven features, though potential adjustments to service structures could occur.
AI and Automation Advancements: Smartsheet is expected to introduce new AI-powered tools to enhance workflow efficiency.
Potential Pricing Adjustments: Private equity ownership often leads to reevaluated pricing models. While no immediate changes have been announced, customers may see modifications in subscription tiers.
Long-Term Product Development: The Smartsheet acquisition provides the company with financial backing to innovate further, but its long-term direction will depend on the priorities set by Blackstone and Vista.
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While private equity ownership brings financial discipline, it may also introduce shifts in corporate culture and management strategies.
For Competitors in the Work Management Market
The Smartsheet acquisition could have implications for competitors such as Asana, Monday.com, and Atlassian.
Increased Market Competition: Backed by Blackstone and Vista, Smartsheet may enhance its enterprise positioning, prompting rivals to strengthen their offerings.
Potential Industry Consolidation: The deal signals a trend of private equity investments in SaaS, which could lead to more mergers and acquisitions.
Shifts in Market Strategy: Competing vendors may need to refine pricing models, introduce new integrations, or differentiate their AI capabilities.
With AI and automation becoming key drivers of innovation, competitors will likely accelerate their technological advancements to remain competitive.
Analyst’s Take on the Smartsheet Acquisition
The Smartsheet acquisition by Blackstone and Vista Equity Partners presents both opportunities and challenges as the company transitions to private ownership. While increased financial flexibility could support long-term innovation, a shift in strategic priorities—such as profitability and operational efficiency, may influence its future direction.
Smartsheet’s Future Under Private Ownership
The Smartsheet acquisition presents both opportunities and challenges. While private ownership offers financial flexibility to pursue long-term innovation, new priorities, such as profitability and operational efficiency could shape Smartsheet’s future direction.
Key factors influencing its trajectory include:
Operational Adjustments: Changes in pricing, service structures, or internal processes could affect users and employees.
AI and Automation Integration: Continued advancements in AI-driven tools could reinforce Smartsheet’s market position.
Expansion Strategy: The company may focus on international markets and enterprise growth.
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Regulatory Scrutiny: Large technology deals sometimes face regulatory reviews, particularly regarding competition.
Customer Adaptation: If service models change significantly, user retention could be impacted.
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What does the Smartsheet acquisition mean for its customers?
With Smartsheet now under the ownership of Blackstone and Vista Equity Partners, customers can expect continued investment in AI and automation-driven features. However, private equity ownership may also bring changes to pricing models and service structures over time. While no immediate modifications have been announced, customers should stay informed about potential updates to subscription tiers and product offerings.
How will the Smartsheet acquisition impact employees?
The transition to private ownership could lead to organizational shifts at Smartsheet. Increased investment in AI and automation may create new opportunities for teams focused on product development, but there is also the possibility of operational restructuring. Private equity acquisitions often involve efforts to streamline costs and improve efficiency, which may result in adjustments to workforce roles or management strategies.
How does the Smartsheet acquisition affect the competitive landscape?
The acquisition positions Smartsheet as a stronger competitor in the work management software market, potentially challenging companies like Asana, Monday.com, and Atlassian. With financial backing from Blackstone and Vista, Smartsheet may expand its enterprise reach and enhance AI-driven capabilities. This move also reflects a broader trend of private equity firms investing in SaaS companies, which could lead to further consolidation and shifts in market dynamics.
At its Analyst Day 2025, Zoho Corporation outlined its vision for enterprise automation, emphasizing Agentic AI and IoT-driven business solutions. The company’s latest advancements indicate a shift toward task-specific AI agents and an expanded IoT ecosystem. This positions the company as a key player in AI-powered enterprise software. While many technology companies focus on large, generalized AI models, Zoho has adopted an industry-specific approach. It is developing lightweight AI agents tailored for automation, security, and real-time decision-making. According to the company, these Agentic AI systems offer greater adaptability and explainability compared to traditional AI models.
Alongside AI developments, Zoho introduced new IoT solutions for manufacturing, smart buildings, energy management, and connected OEMs. It has fully integrated these solutions with its software suite and enabled support for third-party applications. This expands their use cases across various enterprise environments. The event also brought leadership changes, with co-founder Sridhar Vembu transitioning to Chief Scientist. He will focus on AI research and innovation. Meanwhile, Shailesh Kumar Davey, another co-founder, was appointed CEO, ensuring continuity in Zoho’s long-term strategic direction.
This article provides a detailed breakdown of Zoho’s key announcements and their implications for enterprises. It also includes an analyst’s perspective on opportunities, challenges, and future predictions for Zoho and its customers.
Breakdown of Key Announcements
Zoho Analyst Day 2025 brought several strategic updates, highlighting the company’s focus on AI, IoT, and enterprise automation. From leadership transitions to the introduction of Agentic AI and expanded IoT capabilities, Zoho’s latest developments signal a strong commitment to innovation. The following sections provide a detailed look at Zoho’s key announcements and their potential impact on businesses.
Leadership Transition and Strategic Vision
Zoho has undergone a major leadership transition, with former CEO Sridhar Vembu becoming Chief Scientist. He will focus on AI research and deep-tech innovation. Meanwhile, Shailesh Kumar Davey, a co-founder of Zoho, has been promoted to CEO. This is ensuring continuity in leadership as the company accelerates its AI and IoT expansion. This shift reflects Zoho’s long-term commitment to AI development, reinforcing its strategy to stand out through practical, industry-driven AI solutions. Unlike competitors investing in large-scale generative AI models, Zoho is prioritizing Agentic AI. It is smaller, task-specific AI agents designed for real-world business applications.
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Zoho has introduced its next-generation Agentic AI framework, marking a significant step forward in its artificial intelligence capabilities. The company’s AI evolution has progressed through several stages, beginning with Proactive AI, which focused on basic automation. It was followed by Prescriptive AI, designed for recommendation-based intelligence. This was later expanded with Generative AI, enabling content creation and workflow automation. The latest development, Agentic AI, brings AI-driven decision-making and autonomous agents capable of operating independently in business environments. Unlike large, compute-intensive AI models, Zoho’s approach prioritizes specialized, task-specific AI agents designed for practical, real-world applications.
Core advantages of Zoho’s Agentic AI approach:
Task-Specific AI Agents: These agents handle specific tasks like decision-making, automation, and workflow optimization.
Explainability & Testability: AI decisions are not just automated but also verifiable through machine-checkable logic, making them more reliable for enterprises.
No-Code AI Customization: Businesses can train AI agents without needing extensive technical expertise, accelerating adoption.
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Zia Agent Studio: A no-code AI builder that allows businesses to create and customize AI agents without programming knowledge.
Zia Agent Marketplace: A repository of over 1,500 prebuilt AI models, making it easy for companies to deploy AI agents with minimal setup.
Zoho’s Retrieval-Augmented Generation (RAG) AI architecture allows AI to learn from real-time data instead of relying on large, pre-trained datasets, reducing bias and improving accuracy.
IoT Expansion: Industry-Specific Solutions
Zoho has announced a significant expansion of its IoT capabilities, introducing solutions tailored for industries such as manufacturing, smart buildings, energy management, and connected OEMs. In manufacturing, the company is focusing on industrial IoT solutions that enable predictive maintenance, smart factory operations, and real-time monitoring. For smart buildings, Zoho is offering energy-efficient automation, security management, and remote monitoring solutions designed for commercial infrastructure. In the energy sector, its AI-driven tools aim to enhance grid monitoring and power optimization for providers.
Additionally, for connected OEMs, Zoho is introducing automated quality control, smart supply chain monitoring, and equipment analytics to improve operational efficiency. To ensure seamless integration, Zoho’s IoT ecosystem now supports over 40 communication protocols, including MQTT, BACnet, Modbus, Zigbee, and CoAP, enabling compatibility with a broad range of enterprise systems.
Integration with Zoho and Third-Party Applications
Zoho’s AI and IoT solutions integrate seamlessly with its applications, including Zoho CRM, Zoho Analytics, Zoho Creator, and Zoho Desk. Businesses can also connect Zoho’s AI agents to SAP, Oracle, and Salesforce through API integrations for broader interoperability..The platform is built for scalability, allowing enterprises to deploy AI-driven automation across multiple departments and workflows, enhancing efficiency and operational flexibility.
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Zoho has implemented end-to-end encryption across its AI and IoT-driven automation to enhance data privacy and security. In addition, device authentication mechanisms have been introduced to prevent unauthorized access and ensure system integrity. The company is also working toward compliance with major global security frameworks, making its solutions suitable for highly regulated industries such as finance, healthcare, and government.
Future Roadmap: AI-First Vertical Strategy
Zoho is refining its vertical sales strategy by focusing on industry-specific AI solutions to drive enterprise adoption. As part of this effort, the company is developing AI-powered GenAI chatbots that will enable businesses to simplify AI and IoT deployment through natural language interfaces. Looking ahead, Zoho aims to enhance its AI-first approach across all enterprise applications, making automation more intuitive, efficient, and secure.
Analyst’s Take
Zoho’s approach to Agentic AI and IoT integration reflects a strategic focus on enterprise-centric automation, distinguishing itself from competitors that emphasize generalized AI models. By developing task-specific AI agents and expanding secure, scalable IoT solutions, the company is positioning itself within the enterprise software market with a more targeted and adaptable approach.
Strengths & Market Opportunities
Structured & Explainable AI Zoho’s Agentic AI framework follows a structured, testable model that prioritizes transparency and verifiability in AI-driven decision-making. This approach addresses concerns related to unpredictable AI outputs, which remain a key challenge for enterprises adopting AI technologies.
Enhanced Enterprise IoT Integration The company’s IoT expansion strengthens its position in industries such as manufacturing, smart infrastructure, and energy management, where real-time monitoring and automation are critical.
IT & Security Expansion Zoho’s ManageEngine portfolio continues to grow, enhancing its credibility in enterprise IT automation and making it a viable competitor in compliance-heavy industries.
Seamless AI Deployment Tools like Zia Agent Studio and Agent Marketplace provide businesses with the flexibility to customize AI models without requiring deep technical expertise, simplifying AI adoption across multiple industries.
Considerations & Challenges for Enterprises
Adoption & AI Maturity Before full-scale deployment, enterprises may benefit from conducting pilot implementations to evaluate the real-world effectiveness of Zoho’s AI agents in specific use cases.
Enterprise System Compatibility Organizations that rely on SAP, Oracle, or Salesforce should assess potential integration complexities when incorporating Zoho’s AI solutions into their existing workflows.
Regulatory & Security Considerations Businesses operating in regulated sectors such as healthcare and finance must carefully examine Zoho’s compliance with industry-specific security standards to ensure data privacy and regulatory adherence.
What the Future Looks Like for Zoho and Its Customers?
Deeper AI Integration Across Zoho’s Software Suite – Zoho is likely to expand its AI-driven automation across core applications, including CRM, analytics, customer support, and finance. The introduction of AI-powered workflows may improve operational efficiency and enhance decision-making for businesses.
AI-First Vertical Strategies for Industry-Specific Adoption – Zoho’s emphasis on industry-focused AI suggests the development of sector-specific AI solutions tailored for industries such as retail, healthcare, manufacturing, and logistics. This aligns with increasing enterprise demand for AI tools designed to address specialized business challenges.
Growth in AI-Powered IoT for Industrial Applications – As part of its IoT expansion, Zoho is expected to focus on applications like predictive maintenance, smart infrastructure, and energy management. AI integration within IoT could enable more efficient, real-time decision-making for industrial operations.
Increased Focus on AI Security and Compliance – With growing enterprise reliance on AI, Zoho is likely to strengthen its security and compliance framework, ensuring data privacy and AI transparency. This could include advanced governance tools that allow businesses to monitor and audit AI-driven decisions.
Evolution of Leadership and Research-Driven AI Development – With Sridhar Vembu shifting to the role of Chief Scientist, Zoho may prioritize AI research and innovation, focusing on secure, explainable AI models rather than black-box automation. This approach could help enterprises build trustworthy AI systems with improved testability.
Expansion into Enterprise IT Management & Security – Through ManageEngine, Zoho is expected to enhance its role in enterprise IT automation and security. This makes it a stronger contender in the IT management space. This move could attract large-scale enterprises looking for integrated AI-powered IT solutions.
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What is Zoho’s approach to AI, and how does Agentic AI differ from traditional AI models?
Zoho has adopted an industry-specific approach by developing lightweight, task-specific AI agents instead of relying on large, generalized AI models. Agentic AI focuses on explainability and adaptability, allowing businesses to automate decision-making and workflows with more transparency and control.
How does Zoho’s IoT expansion benefit enterprises across different industries?
Zoho’s IoT solutions are designed for industries such as manufacturing, smart buildings, energy management, and connected OEMs. These solutions enable predictive maintenance, real-time monitoring, and automated quality control while integrating seamlessly with Zoho’s software suite and third-party applications.
What leadership changes were announced, and what do they mean for Zoho’s future strategy?
Zoho’s co-founder, Sridhar Vembu, transitioned to the role of Chief Scientist to focus on AI research, while Shailesh Kumar Davey was appointed CEO. This leadership shift reinforces Zoho’s commitment to AI innovation and long-term enterprise automation strategies.
SAP has introduced the SAP Business Data Cloud, a new solution developed in collaboration with Databricks, aimed at unifying and governing SAP and third-party data across organizations. The platform integrates data engineering and analytics functionalities, offering businesses a streamlined approach to data management and AI-driven decision-making. Utilizing Databricks’ technology, SAP Business Data Cloud provides real-time insights and supports AI-powered automation. Early adopters, including Henkel, have begun exploring its potential to enhance data infrastructure and support strategic initiatives.
Let’s Break It Down
Introduction of SAP Business Data Cloud: SAP has launched the SAP Business Data Cloud, a data management solution developed with Databricks to unify and govern SAP and third-party data across organizations.
Integration with Databricks: The platform integrates Databricks’ data engineering and AI capabilities, supporting real-time insights and AI-driven decision-making.
Data Product Economy: It introduces the concept of a data product economy, providing business-ready datasets for finance, supply chain, and HR analytics.
Enhanced AI Capabilities: SAP Business Data Cloud automates workflows and enhances decision-making through AI, including deeper cross-functional insights with SAP’s Joule AI copilot.
Real-Time Data Integration: The solution enables real-time data integration, reducing the need for complex transformations.
Early Adopters: Companies such as Henkel are exploring its potential to optimize data infrastructure and support strategic initiatives.
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SAP has introduced “Business Unleashed,” a new strategy that includes a cloud-based Business Suite integrating functional modules along process chains. This builds on the company’s existing on-premises Business Suite and expands its cloud ERP offerings. The move is expected to influence competition among ERP vendors, prompting further innovation in the market. For existing customers, transitioning from on-premises to cloud solutions may present challenges, including potential short-term disruptions.
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SAP’s new strategy emphasizes three core elements: processes, data, and AI. The approach aims to help companies design process chains and prepare data for AI-driven insights. However, smaller vendors could face challenges in keeping pace with SAP’s technological advancements.
Integrated Modules
The cloud-based Business Suite includes integrated modules such as SAP ECC, SAP CRM, SAP SRM, SAP SCM, and SAP PLM. The inclusion of these modules within a unified suite may increase competition for vendors offering standalone applications.
Business Technology Platform
The new Business Suite is built on the BTP platform, which integrates various technology stacks and cloud services to enable end-to-end processes in the cloud. This foundation provides a unified platform for business operations, reinforcing SAP’s position in the market.
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SAP introduces the SAP Business Data Cloud (BDC) to create a uniform semantic level for data from SAP systems and third-party providers. The introduction of BDC simplifies data management and harmonization, setting a new benchmark for data integration. This development may lead to increased competition among vendors to offer more efficient and user-friendly data management solutions.
AI Integration
The new Business Suite is designed to prepare data for AI applications, supporting data-driven decision-making and process optimization through AI-driven tools.
Customer Hesitation
SAP aims to address customer hesitations about migrating business-critical applications to the cloud with its new SAP Business Data Cloud Suite. The transition may require investment and effort, leading to potential short-term disruptions.
End-to-End Processes
The SAP Business Data Cloud Suite enables the integration of entire user process chains within a single package, offering a comprehensive approach to business operations in a cloud environment.
Analyst’s Take
From an analyst’s perspective, SAP’s introduction of the SAP Business Data Cloud, in collaboration with Databricks is a strategic move that aligns with the company’s growth objectives and industry trends. Here are some key points to consider:
Demand for Cloud Solutions: SAP’s cloud-first approach reflects the increasing demand for cloud solutions in the market.
Unifying Data for AI Analytics: The SAP Business Data Cloud aims to streamline fragmented data by integrating SAP and third-party sources.
Partnership Significance: SAP leverages Databricks’ expertise to enhance the platform’s capabilities.
Scalable Data Management: The platform supports flexible data management across SAP and third-party systems.
User Experience: Early feedback highlights an intuitive interface, efficient workflows, and improved decision-making.
What Should You Know As An ERP Buyer?
Overall, this is very exciting news for both enterprise software buyers as well as SAP. With this alignment, enterprise software buyers receive pre-built and pre-integrated data connections populating the majority of SAP datasets as well as third-party industry standards. Databricks is a market-leading platform among data platform providers without requiring an army of data engineers to build enterprise decision support workloads. But some considerations for buyers as they plan to take advantage of SAP Business Data Cloud offering.
Implementation Challenges: Transitioning to a technology, even if it is pre-baked, requires careful planning due to complexities in data migration, system integration, and user training.
Data Security: Businesses must implement strong security measures to protect sensitive information and comply with data protection regulations.
Vendor Lock-In: With the proprietary IP sitting on top of Databricks from SAP, buyers need to understand their vendor lock-in obligations especially if they don’t prefer as much vendor lock-in.
Cost Considerations: While cloud solutions may reduce infrastructure costs, expenses related to implementation, subscription fees, and maintenance should be evaluated.
Customization Limitations: The data applications don’t impact the operational state as much, but the underlying data structures must support the end-to-end data flows to work and the decision support system to work effectively.
Resistance to Change: Employees may be hesitant to adopt a new system, requiring effective change management and training programs.
FAQs
What is SAP Business Data Cloud, and how does it benefit organizations?
SAP Business Data Cloud is a data management solution developed in collaboration with Databricks to unify and govern SAP and third-party data. It enables businesses to integrate, analyze, and leverage AI-driven insights for better decision-making, real-time analytics, and streamlined workflows.
How does SAP Business Data Cloud support AI and automation?
The platform integrates AI capabilities, including SAP’s Joule AI copilot, to automate workflows, enhance decision-making, and provide deeper cross-functional insights. It also enables real-time data integration, reducing the need for complex transformations.
What challenges should businesses consider before adopting SAP Business Data Cloud?
Organizations may face challenges such as data migration complexities, system integration efforts, potential vendor lock-in, and employee adaptation. Strong security measures, cost evaluations, and effective change management strategies are crucial for a smooth transition.
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