ERP

At Enterprise Connect 2025, NICE unveiled what it calls an “industry-first” orchestration platform aimed at reimagining how businesses manage customer service workflows. Dubbed the NICE Industry First Solution, the newly introduced CXone Mpower Orchestrator offers a comprehensive approach to automating customer interactions by integrating third-party applications, coordinating workflows, and embedding artificial intelligence (AI) across processes.

The announcement of the NICE Industry First Solution has created a stir among contact center and customer experience professionals, largely because of its potential to simplify complex systems and unify fragmented service environments. Here’s a detailed look at what this development means for the industry, how the solution works, and what experts are predicting for its impact on stakeholders and NICE as a company.

Breakdown of the Announcement of NICE Industry First Solution

Seamless Orchestration with AI at the Core

At the heart of the NICE Industry First Solution is the ability to orchestrate workflows across multiple systems, connecting NICE’s own CXone CCaaS platform with third-party tools. The solution is layered over CXone—NICE’s reengineered cloud contact center platform—allowing it to act as a central control system for customer service operations.

Over the past two years, NICE has been embedding AI deeply into its infrastructure, including its proprietary Enlighten AI. The launch of Mpower Orchestrator signals a further evolution of that vision. By not only embedding AI but also orchestrating interactions across platforms, NICE aims to eliminate the silos that typically plague customer service systems.

The NICE Industry First Solution also promises dynamic process analysis and optimization. It proactively identifies performance gaps and implements improvements, creating a self-evolving ecosystem of customer experience.

Addressing the Issue of Siloed Workflows

Traditional customer service setups often rely on various unconnected platforms. This leads to operational silos, delayed resolutions, and a disjointed customer experience. According to Elizabeth Tobey, VP of Marketing at NICE, these issues have long complicated service delivery.

The NICE Industry First Solution tackles this head-on by integrating AI-driven processes across all systems. By aligning workflows, agents, and data into a cohesive unit, the platform aims to deliver a more seamless, responsive service environment.

Key Features that Set It Apart

NICE has packed the CXone Mpower Orchestrator with features designed to provide both visibility and control over service operations. Each feature is built to either enhance efficiency or optimize customer experiences.

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Workflow Insights

This feature offers a complete view of operational metrics like volume, automation levels, containment, and resolution rates. Using Enlighten AI, the system identifies potential issues and offers real-time solutions. Thus, empowering service leaders to act immediately.

Workflow Orchestrator

Through historical and real-time data analysis, this tool recommends changes that involve both AI and human agents. Suggested optimizations can be tested before implementation, allowing for evidence-based decision-making.

Autopilot Conversation Flow

Instead of manually creating automated conversations, this component uses past successful interactions to develop workflows. This not only ensures best practices are followed but also allows the system to continually refine its responses.

Reverse Feedback and Experience Memory (XM)

Human agents can directly provide feedback on AI performance, which the system uses to improve future responses. Meanwhile, XM compiles a comprehensive view of each customer interaction, supporting proactive improvements across operations.

Usability and Human-Centered Design

One notable advantage of the NICE Industry First Solution is its intuitive design. Styled like a copilot, the platform does not require extensive training. NICE emphasizes that ease of use was a central design consideration, ensuring teams can adopt the tool quickly and efficiently.

Expert Endorsement and Industry Buzz

The NICE Industry First Solution has already caught the attention of analysts. Sheila McGee-Smith, President of McGee-Smith Analytics, highlighted the importance of the launch at Enterprise Connect 2025. She noted that the platform enables full customer journey orchestration—from self-service through live agent interaction to workflow completion, all on a single interface built on AI. She emphasized that each AI-assisted interaction can help improve the next, creating a feedback loop that continuously refines customer engagement.

Analyst Take: Impact on Stakeholders and the Market

For Contact Centers

The NICE Industry First Solution could be a game-changer. For years, service leaders have been overwhelmed by a clutter of disconnected AI tools that add complexity rather than reducing it. This orchestration solution aims to unify those scattered elements into a single, intelligent system—making it easier to manage, monitor, and optimize customer service workflows.

For Agents

With improved workflow automation and AI-assisted support, agents may find themselves relieved of repetitive tasks and better equipped to handle complex interactions. Feedback mechanisms also allow agents to directly shape how AI supports them.

For Customers

Faster issue resolution, more consistent experiences, and fewer disjointed handoffs are likely outcomes. As automation becomes more refined, customers can expect a smoother and more personalized interaction journey.

Market Outlook and Future Predictions

The launch of the NICE Industry First Solution marks a significant step forward for both NICE and the broader CCaaS industry. As AI continues to permeate every layer of customer service, orchestration tools like Mpower Orchestrator could become essential components of modern service strategies.

NICE’s recent introduction of an AI Calculator—meant to show businesses how much time and money they can save using AI—complements this move. It suggests that the company is positioning itself as not just a vendor but also a thought leader in AI-powered customer experience.

Going forward, it’s likely that other vendors will respond with their own orchestration platforms, potentially leading to a wave of innovation across the industry. However, NICE’s head start and focus on usability may give it a lasting competitive edge.

FAQs

SAP has expanded its AI assistant, SAP Joule, making it available for developers within its ecosystem. Previously introduced for business users in core SAP cloud products, SAP Joule now supports a wider range of users across SAP Build Process Automation, SAP Build Apps, SAP Build Code, and ABAP Cloud. The goal is to improve developer productivity by providing AI-driven assistance specifically tuned for SAP environments. Here’s a detailed breakdown of the announcement, its potential impact, and key industry insights.

SAP Joule’s Expansion for Developers

SAP initially launched Joule to help business users interact with SAP applications through natural language prompts. The company has now extended this capability to technical users, specifically developers, aiming to streamline the software development process across its platforms. Joule assists developers with several tasks, including:

• Writing code in Java, JavaScript, and ABAP
• Creating user interfaces for applications
• Building data models and generating sample data
• Refactoring and improving existing code
• Writing unit tests for newly developed features

It also helps automate workflows by generating business rules from simple instructions. By analyzing input prompts, Joule suggests relevant templates and patterns from a library of over 400 prebuilt SAP applications. According to SAP, Joule is not designed to replace developers but to serve as an intelligent assistant that enhances developer productivity without removing the need for human expertise.

Specialization Within SAP Environments

Unlike general-purpose AI tools, SAP Joule is specifically trained to understand SAP’s platforms, standards, and programming practices. This specialization enables it to provide more accurate and relevant support compared to broader AI assistants that may lack enterprise-specific context.
In SAP Build Code, for example, Joule assists with coding best practices and security considerations unique to SAP’s environment. For ABAP Cloud, it offers suggestions aligned with SAP’s clean core principles, ensuring that generated code maintains compatibility and upgradability.

SAP has introduced internal validation and guardrails within Joule to minimize AI hallucinations and enhance output quality. This is critical because enterprise development requires a higher level of trust, precision, and compliance compared to consumer applications.

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Analyst’s Take on SAP Joule

Industry analysts have responded positively to SAP’s extension of Joule into developer tools. Arnal Dayaratna, Research Vice President of Software Development at IDC, commented, “What SAP is doing is providing an AI-based developer productivity assistant that’s specialized for their development environments.”

Jason Andersen, Principal Analyst at GigaOm, noted, “The expansion of Joule into SAP Build Process Automation and SAP Build Apps is a smart move that will help developers across the skill spectrum.“

Analysts have highlighted that the biggest advantage of Joule is its deep integration into SAP’s development ecosystem, offering developers AI help that understands the specific frameworks, business processes, and governance models used by SAP customers.

Impact on Stakeholders

The rollout of SAP Joule for developers impacts multiple groups within the SAP ecosystem:

• Developers: With access to AI-assisted coding, testing, and automation, developers can expect reduced development cycles, fewer repetitive tasks, and more time to focus on complex problem-solving.
• Business Users and Project Managers: Faster development timelines and enhanced automation capabilities will enable quicker delivery of business solutions.
• SAP Customers: Organizations using SAP solutions can benefit from more reliable and faster deployment of custom applications and automations, potentially reducing total cost of ownership.
• SAP Itself: Offering Joule strengthens SAP’s position in the enterprise AI tools market, differentiating it from competitors such as Salesforce’s Einstein and GitHub Copilot.

Future Predictions and Industry Trends

The expansion of SAP Joule fits within a broader trend of creating domain-specific AI assistants rather than relying on generalized AI models. Enterprises increasingly demand AI tools that understand industry-specific language, workflows, and compliance requirements. Looking ahead, SAP is likely to enhance Joule further, deepening its integration with ABAP Cloud and SAP Build solutions. Future updates may introduce new support for cross-application workflows, deeper analytics integration, and multi-language support for global developer teams.

There is also potential for SAP to expand Joule into areas like predictive business process management, AI-driven security auditing, and intelligent debugging. These expansions would align with broader enterprise priorities around AI governance, observability, and resilience. Other vendors in the enterprise technology space are moving in a similar direction, indicating that specialization, trustworthiness, and enterprise readiness will become the defining characteristics of successful AI assistants over the next several years.

Key Considerations and Challenges

While SAP Joule offers clear benefits, certain challenges must be addressed:

• Reliability of Outputs: Despite SAP’s efforts to prevent hallucinations, enterprises will need rigorous validation processes before deploying AI-generated code or workflows into production.
• Security and Data Privacy: As SAP Joule operates within sensitive development environments, ensuring full compliance with GDPR, HIPAA, and other regulatory standards remains critical.
• Developer Training and Change Management: To leverage SAP Joule effectively, developers must be trained not just on usage but also on understanding when to trust, edit, or override AI-generated suggestions.
• Scope and Flexibility: SAP Joule currently focuses on SAP environments. Organizations using mixed vendor stacks or custom cloud architectures might need complementary AI tools outside of SAP’s ecosystem.
• Cost Considerations: As with any AI integration, businesses will need to evaluate the cost-benefit balance, considering licensing, training, and support costs associated with adopting SAP Joule widely across their development teams.

FAQs

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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Analyst’s Take on the Zendesk Acquisition

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.
• Cloud-based Customer Experience Platforms: More businesses are moving away from on-premise solutions to cloud-based contact centers, integrating AI and automation.
• 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

 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.

Addressing Cross-Functional Collaboration Challenges

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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Analyst’s Take: Observations & Implications

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

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.

Business Benefits of ThoughtSpot Analyst Studio

• Faster Decision-Making: Businesses can reduce the time spent on data preparation, enabling quicker insights.
• 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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Target Audience and Usability

Who Can Benefit from ThoughtSpot Analyst Studio?

• 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.

Challenges and Considerations for Buyers

• Integration Complexity: Businesses must ensure ThoughtSpot Analyst Studio integrates smoothly with their existing stack.
• Long-Term Viability: Buyers should assess whether ThoughtSpot’s AI-driven approach aligns with their long-term analytics strategy.

FAQs

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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For Smartsheet Employees

Employees at Smartsheet may experience changes as the company transitions to private ownership.

• Expanded AI and Product Development: With increased investment, teams focused on AI and automation could see greater opportunities.
• Potential Organizational Adjustments: Private equity acquisitions sometimes lead to restructuring efforts aimed at streamlining operations.

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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Broader SaaS and Private Equity Trends

The Smartsheet acquisition reflects a larger movement in which private equity firms are actively investing in SaaS.

• Potential for Market Consolidation: More acquisitions in the SaaS industry could reshape competitive dynamics.
• Recurring Revenue Models: SaaS companies offer predictable revenue, making them attractive investment opportunities.
• AI and Automation Focus: Increasing AI adoption in enterprise software is shaping investment strategies.

Challenges and Risks of the Smartsheet Acquisition

While the acquisition presents several growth opportunities, potential risks include:

• Operational Execution Risks: Ensuring a smooth transition while maintaining innovation will be critical for Smartsheet’s success.
• 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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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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Introduction of Agentic AI

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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Expansion of the Zia AI Platform

Zoho’s Zia AI platform was upgraded with several new tools to help businesses implement AI-powered automation:

• Zia Agents: AI-powered assistants designed to handle industry-specific business tasks.
• 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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Security and Compliance in AI & IoT

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?

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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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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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Introduction of SAP Business Data Cloud

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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Core Elements: Processes, Data, and AI

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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Business Data Cloud

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.

1. 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.
2. Data Security: Businesses must implement strong security measures to protect sensitive information and comply with data protection regulations.
3. 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.
4. Cost Considerations: While cloud solutions may reduce infrastructure costs, expenses related to implementation, subscription fees, and maintenance should be evaluated.
5. 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.
6. Resistance to Change: Employees may be hesitant to adopt a new system, requiring effective change management and training programs.

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