Results

2025 in review: AI trends from the buy side and sell side

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

As CxOs zoom out on 2025, it's clear that the year was characterized by AI building blocks and the need for real returns. Agentic AI platforms aren't quite mature, but the industry standards and connections are making deployments more realistic.

If you're an enterprise technology buyer the onus is on the vendors for showing value and more than proof of concepts. The game for both the buy side and the sell side revolves around use cases that show returns and can scale across the enterprise.

For vendors, the appeal of this use-case-by-use-case motion is selling a platform that can create, manage and orchestrate AI agents. For CxOs, the chase is the autonomous enterprise and efficiency and productivity gains that can fund more AI efforts.

In many respects, 2025 was a tale of two halves. The first half was dominated by economic volatility and skepticism about what vendors were pitching.

In the second half, the vendor platforms matured and proofs of concepts began to move to production. There also seems to be consensus that AI, automation and process are comingled.

Get Constellation Insights

For the 2025 analysis, I homed in on all the Constellation Insights articles posted throughout the year and analyzed the broad themes in enterprise technology, the buy side and the sell-side vendors.

Common themes in 2025

Agentic AI grew up, but still isn't what any reasonable executive would call mature. Agentic AI is a heavy lift that includes forward-deployed engineers, an enterprise data strategy that works, services and use case refinement. Simply put, it's easy to build an AI agent. Scaling them with guardrails and building enough trust to let these models run your company is another matter entirely.

AI economics in flux. Salesforce's recent move to offer an agentic enterprise license agreement is notable because it gives enterprises predictability. The consumption approach from SaaS didn't work out for many buyers. Vendors want to monetize the value they're creating, but enterprises are tired of bills continuing to rise. A consensus emerged that there will be multiple models that are combined to optimize for price performance. Hyperscalers are working custom silicon to commoditize compute and models will be rightsized for the task at hand.

Everything is a platform. SaaS providers are branching out beyond their core markets to become broader AI agent platforms. There isn't a vendor that doesn't have a horse in the AI agent platform race.

The real wins will revolve around industry-specific use cases and first-party data. Enterprises are beginning to leverage their unique data to train models and optimize use case by use case and industry by industry. Context is everything. Again, it's easier said than done.

The buy side

AI is an excuse to change operating models. Enterprises are beginning to use the agentic AI push as a way to optimize operations across all processes and use cases. These efforts would take longer under yesterday's transformation projects, but AI is giving smart companies air cover to accelerate plans.

Models are a commodity. Enterprises are no longer wowed by the latest and greatest models. China's DeepSeek and Qwen from Alibaba changed that proprietary model thinking in early 2025. Now enterprises are just as likely to use Nova models from AWS or open source as they are the big three models. That said models are a key ingredient of buying decisions of broader platforms.

Multi-cloud, multi-model, multi-everything. Enterprises have always been wary of lock-in (and still do it anyway), but AI is advancing so quickly that CxOs want neutrality and options. Interoperability is a requirement and AWS, Google Cloud and Microsoft Azure are beginning to connect. AI sprawl isn't a concern yet, but will be soon.

Technology strategy and business strategy merge. Spend on infrastructure, applications, models and ecosystems are driven by margins, agility and resilience of all types. Enterprises will look to AI as a way to abstract away technical debt.

Value over vision. Enterprises are shrinking budget cycles and demanding measurable impact. Enterprises care about efficiency, productivity, customer experiences and revenue gains. Vanity pilots are kaput. Practical AI is in.

It's still all about data. The enterprises that have a coherent data strategy, data quality and modern pipelines and platforms can win in the AI age. Too few enterprises have their data game down.

The sell side

Every vendor wants to be your sole platform. A tenured CxO would chuckle at these AI vendor developments. Why? Vendors have always wanted to consolidate all of your spending with them. Picking a vendor that can be your one go-to agentic AI platform isn't easy.

The value sales pitch. Vendors increasingly talked enterprise value, use cases and process optimization. They're certainly talking a good game. By mid-2025, this value-based sales pitch became the norm. Enterprise vendors and even OpenAI and Anthropic are all using the industry and use case playbook with partners or via direct sales.

LLM giants build ecosystems. OpenAI and Anthropic, not to mention Google's Gemini, are building ecosystems and applications that can leverage their models. What's unclear is whether these LLM giants can be the overarching interface that relegates enterprise software to plumbing. Also keep an eye on Databricks and Snowflake, which could leverage their data platforms to be the overarching enterprise layers.

Orchestration is the big thing. Vendors are pitching themselves as your go-to AI orchestration layer. For a vendor, agent orchestration will drive stickiness and revenue and lock-in. It's also possible that orchestration and data gravity will go together and drive vendor revenue.

Hyperscalers gain clout. Aside from ServiceNow, hyperscalers and integrators are the most natural fit to be that overarching AI platform, abstraction and orchestration layer. The big three cloud players are horizontal, touch every part of the enterprise and have pricing models that naturally go together with AI agents. Add it up and AWS, Microsoft Azure and Google Cloud all gained clout in 2025.

The year in Insights

Data to Decisions Future of Work Innovation & Product-led Growth New C-Suite Next-Generation Customer Experience Chief Executive Officer Chief Financial Officer Chief Information Officer

ServiceNow makes its cybersecurity move, acquires Armis for $7.75 billion

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

ServiceNow acquired Armis, a cybersecurity exposure management company, for $7.75 billion in cash in a move that will triple the company's addressable market in security.

For ServiceNow, the Armis deal expands its cybersecurity reach and can accelerate growth for its Security, Risk and Operations Technology (OT) portfolio, which delivered more than $1 billion annual contract value in the third quarter. Armis flagship offering is Centrix, a cyber exposure management platform that has real-time visibility, risk assessment and proactive protection. Centrix aims to secure IT, OT, internet of things and medical devices.

Armis has more than $340 million in annual recurring revenue and growth of 50%. Armis, founded in 2015, has about 950 employees that will join ServiceNow.

ServiceNow will be able to integrate Armis Centrix with its AI agents and workflow tools. ServiceNow Autonomous Risk and Security aims to unify cybersecurity and risk operations on one platform. â€œAutonomous IT only works if platforms can see, decide, and act in one system. Armis gives ServiceNow the ‘see’ layer it needed to make that vision credible," said Constellation Research analyst Chirag Mehta. 

Armis, which competes with Nozomi Networks, Claroty, Dragos, Microsoft, Palo Alto Networks and Fortinet among others, is on multiple Constellation Shortlists:

With the Armis deal, ServiceNow also gets a cybersecurity platform that reaches multiple industries including manufacturing, telecom, retail, logistics, automotive, energy and health care. Armis also has a public sector footprint.

In a statement, ServiceNow said the plan is to create a unified security exposure and operations stack. Amit Zavery, president, chief operating officer and chief product officer at ServiceNow, said "together with Armis, we will deliver an industry-defining strategic cybersecurity shield for real-time, end-to-end proactive protection across all technology estates."

Yevgeny Dibrov, co-founder and CEO of Armis, said ServiceNow will help its security platform scale.

ServiceNow said Armis will provide cybersecurity data to ServiceNow AI Control Tower, which manages and governs enterprise AI, and pair up with various components of the ServiceNow AI Platform.

Constellation Research's take

Mehta handicapped the ServiceNow and Armis deal and the implications. 

“ServiceNow’s acquisition of Armis reflects a clear recognition that workflow orchestration alone is no longer sufficient to manage cyber risk in an AI-driven enterprise. As AI adoption expands the attack surface beyond traditional IT into operational technology, medical devices, and unmanaged assets, ServiceNow needed deeper, real-time visibility into what is actually connected and exposed. Armis fills this gap by bringing continuous, agentless asset intelligence and exposure management that extends across IT, OT, and cyber-physical environments. The strategic value lies in pairing Armis’ real-time exposure context with ServiceNow’s ability to prioritize, govern, and act through workflows, moving customers from reactive security operations toward measurable, continuous risk reduction. This deal positions ServiceNow to compete not as another security point product, but as an AI-native control plane where exposure intelligence is directly translated into enterprise action.

ServiceNow had already established itself as a strong orchestration layer for security, risk, and IT operations, supported by CMDB and AI-driven workflows. However, it depended heavily on external tools for asset discovery and exposure data, especially for unmanaged, non-IT, and cyber-physical environments. This created a structural gap: ServiceNow could route and govern work, but it did not natively “see” the full attack surface with sufficient fidelity or timeliness to support autonomous decision-making. Armis brings precisely what ServiceNow lacked: real-time, agentless discovery and classification across IT, OT, IoT, and medical devices, combined with deep exposure analytics. Its strong adoption across Fortune 100 enterprises and public-sector organizations demonstrates that this capability is already trusted at scale.”

More:

Data to Decisions Future of Work Digital Safety, Privacy & Cybersecurity Innovation & Product-led Growth Tech Optimization Next-Generation Customer Experience AI GenerativeAI ML Machine Learning LLMs Agentic AI Analytics Automation Disruptive Technology cybersecurity Chief Information Officer Chief Information Security Officer CISO Chief Privacy Officer Chief AI Officer CAIO CXO

HCLSoftware’s Actian acquires Wobby, Jaspersoft as it builds out data platform

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

HCLSoftware said it will acquire Wobby, a startup focused on providing AI agents for data platforms and combine it with its Actian unit. Separately, HCLSoftware said it’s acquiring Jaspersoft from Cloud Software Group in a deal to build out Actian’s agentic AI toolset.

Terms of the deals weren't disclosed

Actian, the data and AI division of HCLSoftware, is seeing strong demand for its metadata, data catalog and governance tools. Wobby will bring an agentic AI data analyst to Actian so customers can get insights on complex datasets quickly.

HCLSoftware added that Wobby will accelerate its data engineering roadmap.

Wobby features a natural language interface, a proprietary semantic layer and architecture that interprets context and automates complex workflows. Wobby will complement the knowledge graph in the Actian Data Intelligence Platform.

Actian CEO Marc Potter said in a statement that Wobby will give the company's platform an "LLM-powered natural-language analytics on a unified, governed semantic layer, enabling self-service analytics."

Wobby has multiple integrations including Snowflake, Databricks, Collibra, Cube, Microsoft Data Fabric, Google Big Query and Amazon Redshift. Wobby's flagship AI agent is its Deep Analysis Agent that aims to provide multi-angle analysis on data even with basic prompts using a multi-agent architecture.

The acquisition is expected to close in February.

HCLSoftware’s acquisition of Jaspersoft followed the Wobbly announcement.

Jaspersoft, a unit of Cloud Software Group, provides analytics and a reporting platform. Jaspersoft will be folded into Actian.

With Jaspersoft, Actian will be able to accelerate its data management experience plans with interactive dashboards, advanced visualizations and reporting. Jaspersoft also brings a developer base of data engineers and architects.

The Jaspersoft purchase is expected to close within six months of signing.

Data to Decisions Chief Information Officer

Alphabet buys Intersect for $4.75 billion to boost its data center energy options

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Alphabet said it will acquire Intersect, a startup focused on energy for data centers, for $4.75 billion and the assumption of debt. Google, a unit of Alphabet, owns a minority stake in Intersect.

Last year, Intersect announced a partnership with Google and TPG Rise Climate to scale renewable power and storage for new data centers.

As cloud providers, notably Google Cloud, AWS, Microsoft Azure and Oracle, scale data centers power becomes the largest hurdle.

In a statement, Alphabet said that Intersect will remain separate from the company and Google. However, Intersect will work with Google's technical infrastructure team to develop projects. Intersect and Google are already collaborating on a co-located data center and power site in Haskell County, Texas.

The focus of the deal is on new assets and don't include Intersect's existing assets in Texas and California. Those Intersect assets will remain independent with the company's existing investors. Sheldon Kimber, CEO of Intersect, will continue to lead the company. Intersect has $15 billion of infrastructure operating or under construction and plans to have 10.8 GW in construction or operating by late 2028. Intersect also has partnerships with Tesla and First Solar as well as Google.

According to Alphabet and Google CEO Sundar Pichai, Intersect will "will help us expand capacity, operate more nimbly in building new power generation." Alphabet and Google said Intersect will augment its energy efforts underway with utilities and energy developers.

"For a long time we thought the AI race was all about the GPUs, but Alphabet's investment in Intersect makes it clear - it's all about energy. Without energy, there's no data center, no GPUs (or TPUs for Google) and no AI," said Holger Mueller, an analyst at Constellation Research.

In a blog post, Kimber said:

"AI today is stuck behind one of the slowest, oldest industries in the country: electric power. The country has racks full of GPUs that can’t be energized because there isn’t enough electricity for them. The grid is a patchwork operating system that’s been running for a century. An engineering miracle in its time but not built for the AI era.

America deserves a better business model for electricity. That model is increasingly ​'bring your own generation.'"

Data to Decisions Tech Optimization Google Big Data Chief Information Officer CIO CTO Chief Technology Officer CISO Chief Information Security Officer CDO Chief Data Officer

Paychex: How it's playing AI on multiple fronts

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Paychex is betting that its proprietary data sets in human capital management and adjacent markets will make it a winner in AI via productivity and new products.

The company reported better-than-expected second quarter earnings driven by its acquisition of Paycor, announced a year ago, and AI-driven efficiencies. Paychex reported second quarter earnings of $1.10 a share on revenue of $1.56 billion, up 18% from a year ago. Non-GAAP earnings were $1.26 a share.

For fiscal 2026, Paychex is projecting revenue growth of 16.5% to 18.5%. Paychex CEO John Gibson said the company now expects to save $100 million in expenses via the Paycor integration.

Along with the earnings results, Paychex outlined its AI plans and its positioning. The company recently launched agentic AI tools to automate payroll processing, created a knowledge mesh system that organizes unstructured data such as calls and emails into a searchable network and layered generative AI throughout its platform.

Here's a look at the takeaways from Gibson on Paychex earnings call and cover multiple AI disruption points.

AI employment disruption. Paychex business depends on employees and there's a risk that AI will mean less employment and revenue for the company. Gibson said more than 70% of its customers employees work in "blue and gray-collar industries" that are harder to displace. In addition, the Paychex customer base skews SMB where staff where multiple hats. Those roles are harder to replace with AI.

"If AI disrupts large firms disproportionately, talent may shift to smaller businesses, benefiting our clients. Meanwhile, our clients continue to face talent shortages and AI can help improve efficiencies to address those gaps," said Gibson.

Simply put, there’s a valid case that AI disruption at large companies is going to mean that reskilling efforts will need to go well beyond AI and into entrepreneurship.

The Paychex revenue model. Gibson said that Paychex has a revenue model that has a significant fixed base fee component and that historically has insulated it from employment fluctuations. Paychex also HR experts to go along with the technology platform.

Proprietary data. Gibson said: "In terms of our differentiation, AI success hinges on data quality and data scale. With one of the largest proprietary datasets in the industry, we believe we have a powerful competitive advantage to drive superior AI performance."

This first-party data argument is something you're going to hear across multiple enterprises in technology and beyond. The game is going to be leveraging that data to spin off new products and services, becoming more efficient and building a moat around the business model.

"I think AI is going to be very interesting as we try to productize it. We're going to try to improve the customer experience. We're going to try to add more value to our product to differentiate ourselves because there are very few players that have the depth of insights and information from our data that we can provide inside the technology," said Gibson.

Pragmatic AI applications. Paychex plays in a crowded market where it can compete with ADP, Rippling, Intuit, Trinet, Dayforce and a bevy of others depending on the market. The acquisition of Paycor enabled Paychex to cater to more mid-sized businesses.

Gibson said Paychex is focused on "delivering pragmatic AI solutions focused on measurable outcomes such as time saved and friction removed from everyday processes." An AI-driven employment law and compliance platform would be an example. The company is piloting its first agentic AI tools now.

Holger Mueller, an analyst at Constellation Research, said:

"Paychex is playing with its two offerings Paychex at the lower end and Paycor for enterprises. Being able to serve both markets is attractive and investors are seeing a few more quarters of favorable comparisons thanks to the Paycor acquisition. To position itself for the new set of AI startups, Paychex will have to do more though. Fast growing startups in the past would buy large enterprise systems - larger than needed in many cases - to signal to investors they were ready for massive growth. Paychex will need to continue to appeal to those new companies."

Data to Decisions Future of Work Next-Generation Customer Experience Tech Optimization AI Analytics Automation CX EX Employee Experience HCM Machine Learning ML SaaS PaaS Cloud Digital Transformation Enterprise Software Enterprise IT Leadership HR Chief People Officer Chief Information Officer Chief Customer Officer Chief Human Resources Officer CHRO

DisrupTV’s Top 25 Books of 2025: Leadership, AI, and the Ideas Shaping What Comes Next | DisrupTV Ep. 422

R "Ray" Wang
Principal Analyst and Founder Constellation Research
R “Ray” Wang is the CEO of Silicon Valley-based Constellation Research Inc. He co-hosts DisrupTV, a weekly enterprise tech and leadership webcast that averages 50,000 views per episode and blogs at www.raywang.org. His ground-breaking best-selling book on digital transformation, Disrupting Digital Business, was published by Harvard Business Review Press in 2015. Ray's new book about Digital Giants and the future of business, titled,&nbsp;Everybody Wants to Rule The World&nbsp;was released in July 2021. Wang is well-quoted and frequently interviewed by media outlets such as the Wall Street Journal, Fox Business, CNBC, Yahoo Finance, Cheddar, and Bloomberg. Short Bio R “Ray” Wang (pronounced WAHNG) is the Founder, Chairman, and Principal Analyst of Silicon Valley-based Constellation… Read more
Elle DeRosa
Director of Marketing, Communications & Operations Constellation Research
Elle is the Director of&nbsp;Marketing&nbsp;at Constellation Research and producer of the weekly enterprise tech&nbsp;show,&nbsp;DisrupTV. She leads marketing and communications efforts across all avenues while also managing an array of programs including the SuperNova Awards, Business Transformation 150, AX100, AI150,&nbsp;S50&nbsp;and&nbsp;ShortLists.&nbsp;She has previous experience in public relations and has a strong passion for the marketing world.&nbsp; &nbsp; Contact Elle at [email protected] Read more

DisrupTV’s Top 25 Books of 2025: Leadership, AI, and the Ideas Shaping What Comes Next

The latest episode of DisrupTV marked a milestone moment with the unveiling of the Top 25 Books of 2025—a curated list spotlighting the ideas, frameworks, and leadership principles that will shape organizations, culture, and technology in 2026 and beyond.

Featuring bestselling authors, strategists, and practitioners, the conversation explored how leaders can navigate disruption, build courage, define mission, and co-create with AI in what many are calling the Age of Intelligence.

See the full listing here.

Why the Top 25 Books of 2025 Matter

Books don’t just reflect the times—they help leaders make sense of uncertainty, challenge assumptions, and take action. Since its inception, DisrupTV has featured more than 210 books, and this year’s Top 25 list reflects a world grappling with:

  • Rapid AI acceleration
  • Shifting definitions of leadership and work
  • The need for purpose, courage, and adaptability
  • New approaches to innovation beyond traditional transformation

This year’s authors didn’t just talk about trends—they shared practical guidance for leading through complexity.

Epic Disruptions and Learning From History

Scott Anthony, author of Epic Disruptions, emphasized the importance of studying historical innovation cycles to understand today’s upheavals. His perspective reframes disruption not as chaos, but as an opportunity for curiosity, creativity, and even joy.

Rather than fearing disruption, Anthony encouraged leaders to approach it with a sense of play—recognizing patterns from past transformations to make smarter decisions today.

Honing Over Transforming: A New Leadership Mindset

Steven Goldbach, author of Hone, challenged the traditional obsession with large-scale transformation. Instead, he advocated for continuous honing—small, deliberate adjustments that keep organizations sharp in fast-moving environments.

Using the analogy of chefs honing knives rather than grinding them down, Lochhead made the case that adaptability beats overhaul in an era of constant change. He also called for a return to respectful debate, arguing that progress depends on open, thoughtful disagreement.

Personal Branding for Introverts in a Loud World

Goldie Chan, author of Personal Branding for Introverts, tackled a timely challenge: how thoughtful, quieter leaders can build influence without becoming something they’re not.

In an age dominated by algorithms and attention economies, Chan emphasized that personal branding is about intentional storytelling, credibility, and clarity—not volume. For introverts, managing a personal brand isn’t optional; it’s a leadership skill.

Mission-Driven Leadership and Purpose

Mike Hayes, author of Mission Driven and a former Navy SEAL, brought a powerful message about purpose. His book—and his life’s work—focuses on helping people define their mission, with all book profits supporting Gold Star families.

Hayes underscored that mission-driven leaders create resilience, alignment, and meaning—especially in high-stakes environments. Purpose isn’t abstract; it’s operational.

How to Be Bold: Courage in Uncertain Times

Ranjay Gulati’s How to Be Bold offered practical insights into courage as a leadership discipline—not a personality trait. Gulati emphasized that boldness is built through action, self-efficacy, and values-driven decision-making, even when fear is present.

In a world shaped by AI and ambiguity, courage becomes a competitive advantage.

Brave Together: Co-Creation With AI

Chris Deaver’s Brave Together explored the shift from humans competing with machines to co-creating with AI. Rather than framing AI as a replacement, DeVore positioned it as a collaborator—one that can enhance creativity, leadership, and decision-making when guided ethically.

This theme echoed throughout the episode: the future belongs to leaders who understand how to partner with intelligence, not fear it.

The Age of Intelligence and Super Shifts

Several authors touched on what Steve Fisher described as the Age of Intelligence—a period where machines may outperform humans in narrow tasks, but humans remain essential for judgment, values, and meaning.

Books like The Existing Market Trap, Super Shifts, and Employment Is Dead challenged leaders to rethink assumptions about markets, careers, and organizational design.

Key Themes Across the Top 25 Books of 2025

Across the episode, several themes consistently emerged:

  • Leadership requires courage, self-awareness, and action
  • Continuous improvement beats one-time transformation
  • Mission and purpose drive resilience and performance
  • AI must be co-created with humans, not blindly adopted
  • Personal branding is essential—even (especially) for introverts
  • Ethics, trust, and respectful debate matter more than ever

Final Thoughts: Reading as a Leadership Advantage

As Vala Afshar and R "Ray" Wang noted, knowledge alone isn’t enough—action is what creates impact. The Top 25 Books of 2025 provide context, clarity, and frameworks to help leaders act with confidence in uncertain times.

Whether you’re navigating AI adoption, redefining success, or searching for your next mission, these books offer a roadmap for the year ahead.

DisrupTV closed the episode by thanking its community and encouraging leaders to stay curious, stay bold, and stay human as we head into 2026.

Related Episodes

If you found Episode 422 valuable, here are a few others that align in theme or extend similar conversations:

 

New C-Suite Future of Work Tech Optimization Chief Executive Officer Chief People Officer Chief Information Officer Chief Data Officer Chief Technology Officer
On DisrupTV <iframe width="560" height="315" src="https://www.youtube.com/embed/zrfP62HNnAw?si=gQKTOraL8HwRSX64" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>

FedEx's logistics data spinning up new services, products

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

FedEx is best known as a delivery and logistics company, but with its data footprint and use of AI it’s starting to resemble a technology firm.

On FedEx's second quarter earnings call, President and CEO Rajesh Subramaniam outlined how the company's digital transformation efforts have helped the company execute better. Those technology, data and AI efforts are also likely to lead to new products.

"The reality is that AI is becoming an integral part of all business functions," said Subramaniam, who said FedEx is working to provide its employees with AI knowhow in multiple areas. "We continue to explore new approaches that leverage our real-world operational data platform. We are actively pursuing opportunities to bring digital solutions to the market, starting with logistics intelligence insights."

Subramaniam said a recent partnership with ServiceNow highlights where FedEx is going. Under a partnership announced Oct. 29, FedEx said it will combine its Dataworks platform with ServiceNow to anticipate supply chain disruptions. FedEx Dataworks will also integrate with ServiceNow's procurement applications to provide supply chain performance intelligence and provide insights.

"Through this collaboration, we are giving businesses a single system that anticipates, adapts and acts before they experience supply chain disruptions. And by integrating into ServiceNow's procurement and supply chain solutions, we are beginning to monetize the proprietary insights that only FedEx can provide. Enterprises need access to real-world logistics intelligence to power their AI systems and workflows and this partnership demonstrates market demand for what we have built," said Subramaniam.

The ServiceNow-FedEx platform integrations will start rolling out in the first quarter of 2026.

The FedEx-ServiceNow partnership highlights how companies with strong industry knowledge and datasets can leverage AI to spin up new products. In the FedEx case, data products and software platforms will have much higher margins that the logistics network that is heavy on the capital expenditures yet provides the data that'll create new services.

Other areas where FedEx is spinning up new data-driven products and services:

Data center logistics. Brie Carere, Executive VP & Chief Customer Officer at FedEx, said the company is creating a team focused on data center infrastructure. FedEx is developing vertical strategies in tech as well as automotive and healthcare. The data angle is getting goods to the right place at the right time at scale.

Shipment communications platforms. Carere said: "We are very pleased with how our digital tools are supporting revenue growth while creating better outcomes for our customers and their customers."

She added:

"Wayfair is a great example of how we're using these tools to help our customers improve their shipment-related communications and support their customer service teams. By using our premium integrated visibility tool, Wayfair is increasing their Net Promoter Score, reducing where is my order calls, otherwise known as WISMO calls and decreasing outages with their tracking data."

Data to Decisions Future of Work Next-Generation Customer Experience AI ML Machine Learning LLMs Agentic AI Generative AI Robotics Analytics Automation Cloud SaaS PaaS IaaS Quantum Computing Digital Transformation Disruptive Technology Enterprise IT Enterprise Acceleration Enterprise Software Next Gen Apps IoT Blockchain CRM ERP CCaaS UCaaS Collaboration Enterprise Service developer Metaverse VR Healthcare Supply Chain Leadership Chief Information Officer CIO CTO Chief Technology Officer CISO Chief Information Security Officer CDO Chief Data Officer

Accenture says advanced AI is so pervasive it won’t break it out anymore

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Accenture said that AI is so pervasive in enterprise transformation that it won't break out figures going forward. And although AI is everywhere, Accenture noted that half of the advanced AI projects also require a data project.

The consulting giant broke out advanced AI--a category with generative AI, agentic AI and physical AI--bookings were $2.2 billion in the first quarter, double from a year ago. Accenture also said that it has reached its goal of 80,000 AI and data professionals.

Accenture reported first quarter earnings of $3.54 a share on revenue of $18.7 billion, up 6% from a year ago. For fiscal 2026, Accenture is projecting revenue growth of 2% to 5%.

CEO Julie Sweet explained how AI is now everywhere just like cloud is.

"As we think about the advanced AI opportunity ahead, as you know, we were the first in our industry to share our bookings and revenue from advanced AI, which we define as GenAI, Agentic AI and physical AI and does not include data, classical AI or RPA. "This will be the last quarter in which we share these specific metrics. The demand for AI is both real and rapidly maturing. We've now reached a point where advanced AI is being embedded in some way across nearly everything we do, and many of our clients are focusing on moving beyond standalone proof of concepts or initiatives."

Sweet said the AI disclosure made sense in late 2023 when bookings were $100 million across 100 projects. Today, Accenture has delivered about $11.5 billion in bookings across 11,000 projects with revenue of $4.8 billion. Advanced AI is being deployed in 1,300 of Accenture's 9,000 clients.

Accenture said its focus is scaled projects that integrate multiple forms of AI. In other words, it's difficult to separate AI from broader projects. Sweet said "demand for reinvention remains strong" and transformation projects include both digital core (cloud and data projects) as well as AI and cover everything from manufacturing to finance and insurance to supply chain.

"Starting with the demand environment, clients continue to prioritize their most strategic and large-scale transformational programs, which convert to revenue more slowly but position us at the center of the reinvention agendas. The pace of overall spending and discretionary spend in our market is at the same levels we have seen over the last year," said Sweet.

According to Accenture, AI projects almost inevitably mean data transformation. "When companies tell us they want to use AI, they quickly realize that AI is only as powerful as the data underneath it," said Sweet. "Most organizations have mountains of data spread across systems, stored in different formats, often unreliable or incomplete. Before AI can create value, underlying data and the processes connected to it need to be simplified, cleaned, connected and properly governed."

Accenture is using AI to modernize data platforms and improve quality at scale. Sweet said at least half of the advanced AI projects also require a data project.

Sweet cited projects with Essity and Bristol Myers Squibb as examples of clients leveraging AI agents to automate processes. "The real opportunity is not proving AI works, it is making it work everywhere. Scaling AI means working with all forms of AI and means embedding it across critical processes so it transforms outcomes," said Sweet.

Other takeaways from Accenture's first quarter earnings call:

  • "Enterprise AI is fundamentally different than consumer AI. Consumer AI adoption is instant. In the enterprise, you can't adopt it unless you have the right security. You've done the right work around processes and most companies have fragmented and siloed processes. You have to have the right data and most companies have mountains of data with a lot of issues in the data, and we call it they have process debt, they have data debt. And of course, they need a modern digital core. And that's why so many companies are still early in the journey," said Sweet.
  • Productivity isn't driving AI projects as much. "when you look at our bigger deals over the last quarter, for example, you see that advanced AI is a bigger part of those deals, but you also see that it's both growth and cost because clients are not only fixated on the productivity side. You cannot cut your way to growth. And in this market, they need to find more growth," said Sweet.
  • Banking is leading in AI and finance and procurement are key use cases. Energy and utilities and pharmaceuticals are early in terms of scaling. "There are leaders in every industry who already had strong digital course who are leapfrogging. It's very different than cloud where you have some industries like, say, energy lagging behind for quite some time. It's quite different this time," said Sweet.

Data to Decisions accenture Chief Financial Officer Chief Information Officer Chief Data Officer Chief Technology Officer

HOT TAKE: Salesforce Solidifies Agentic Sales Engagement with Qualified Pickup 

Martin Schneider
Vice President and Principal Analyst Constellation Research
Martin Schneider has had a unique career that has spanned both analyst and marketing practitioner roles, focused on high technology and related industries. The unifying factor has always been both a keen analysis of go-to-market trends, while also having achieved success as a marketing leader. Schneider started his career as a journalist covering B2B technologies, and quickly transitioned into a leading analyst covering application software for the 451 Group in NYC, where he specialized in CRM, marketing automation, and business intelligence/analytics technologies. After analyzing various go-to-market strategies of dozens of technology vendors, Schneider made the move to the vendor side, where he led successful go-to-market teams for several startups and established tech providers,… Read more

Salesforce has made some big M&A investments to make its agentic vision a reality - a la Informatica etc. But sometimes, the smaller deals that actually play into core go-to-market motions can have an outsized effect. This might be the case with the deal Salesforce announced yesterday - acquiring  “agentic marketing” company Qualified. What Qualified offers is a conversational tool set that identifies high-intent website visitors and uses AI agents—most notably their Piper AI SDR —to engage them through chat, voice, or video. By integrating natively with Salesforce, the software aims to allow revenue teams to bypass traditional lead forms, instantly qualifying prospects and booking meetings to accelerate the sales cycle. Now, again this is grat for marketing leaders, but also important for revenue leaders focsued on expansion revenue. By understanding intent inside the install base, foir example, teams can be more proactive and collaborative to secure additional revenue - or simply treat existing customers like they know them - rather than as "just another raw lead." 

At its core, Qualified excels at transforming website visitors into qualified pipeline whether touched by their intelligent chatbots and live sales reps. This capability directly addresses a long-standing challenge for Salesforce: bridging the gap between passive website engagement and active CRM pipeline. While Salesforce provides the system of record and robust sales cloud, the instantaneous, personalized engagement layer on the website was often left to third-party tools. Qualified seamlessly integrates this crucial "last mile" of engagement directly into the Salesforce ecosystem. Also, while Salesforce offers an out of the box BDR agent in its Agentforce arsenal - Qualified brings far more nuance, development, and ability to leverage first-party data and other data and document sources to provide effective back-and-forth communique’ between the agents and prospects. While the Agentforce tool can be quickly deployed and be effective, Qualified brings the game to another level. Again, for existing customer engaging with Piper - they can access more documents and other unstructured data to better solidify their buying plans than a simplistic BANT discovery flow that is offered for new leads accessing the web site, for example. 

By owning the conversational layer, Salesforce gains invaluable first-party data on prospect intent and behavior before they even become a formal lead in the CRM - and in the case of existing business - sometime you simply do not want them to be treated as a "lead.". This rich pre-CRM data fuels more accurate lead scoring, better personalization for subsequent outreach, and a more holistic view of the customer journey, from anonymous visitor to loyal advocate. Again, while Salesforce offers some remedial capabilities in these areas, gaining a more robust set of functions - already built on the Salesforce platform - will be a boon. What will be important is ensuring that both Sales Cloud and Marketing Cloud are the benificiaries of the deeper integration post-merger. While Qualified has been optimized for the Pardot and post-Pardot Marketing Cloud platform, there are key use cases for sales and customer success that can be drilled into and finessed to make these an even bigger slam dunk deal. 

For growth leaders, this should bring more benefits than an eventual consolidation of SaaS bills to pay. The acquisition offers a more unified data picture. From initial website clicks and chatbot interactions to CRM records and sales activities, the entire journey will live more seamlessly within Salesforce.  This comprehensive view is critical for training more effective AI models, optimizing lead routing, and ultimately boosting conversion rates.Revenue leaders must insist on integrated platforms that eliminate data silos to truly understand and serve their buyers.

And of course, ideally, sales reps will spend less time qualifying cold leads and more time engaging warm, pre-vetted prospects handed off directly from the website. This frees up valuable sales capacity for high-value activities, directly impacting pipeline velocity and revenue generation. Leaders should plan for a future where AI handles the initial qualification, allowing their human teams to focus on relationship building and complex deal closure.

For those already using Salesforce but not Qualified, this should bolster the ability to deploy AI-powered GTM strategies and motions. But for those not using Salesforce but were using Qualified?  There are still a number of solid lead management and AI BDR tools to choose from if your organization does not want to shift SFA/CRM platforms. 

Next-Generation Customer Experience Data to Decisions Innovation & Product-led Growth Future of Work Tech Optimization Digital Safety, Privacy & Cybersecurity New C-Suite Sales Marketing salesforce ML Machine Learning LLMs Agentic AI Generative AI Robotics AI Analytics Automation Quantum Computing Cloud Digital Transformation Disruptive Technology Enterprise IT Enterprise Acceleration Enterprise Software Next Gen Apps IoT Blockchain Leadership VR business Marketing SaaS PaaS IaaS CRM ERP finance Healthcare Customer Service Content Management Collaboration Chief Revenue Officer CEO Chief Executive Officer CIO Chief Information Officer CTO Chief Technology Officer CAIO Chief AI Officer CDAO Chief Data Officer CAO Chief Analytics Officer CISO Chief Information Security Officer CPO Chief Product Officer

Zoho launches Zoho Spend, Zoho Billing Enterprise Edition

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Zoho launched Zoho Spend, a spend management application that integrates payroll, accounts payable automation, travel, expense and procurement, and Zoho Billing Enterprise Edition, which is designed to streamline billing operations to recognize revenue faster.

The applications are designed for larger companies and enable smaller ones to scale without leaving the Zoho platform. In addition, Zoho added a series of AI tools in applications across Zoho's Finance and Operations Platform.

Prashant Ganti, Zoho's vice president of global product strategy, development and alliances for the finance and operations unit, said Zoho Billing Enterprise Edition "brings together lot of capabilities that caters to large enterprises, like advanced customer, lifestyle management, lifecycle management and complex pricing models coupled with tools to address regulatory norms."

Ganti said Zoho Billing Enterprise Edition already has customers live including one that is processing 20 million invoices on the platform.

As for Zoho Spend, Ganti said the application is designed to unify the processes behind the money going out of the enterprise. "The application is designed to bring all the disconnected strands of spend in one platform," said Ganti.

Ganti added that Zoho is continually adding AI features across its finance and operations platform to take out manual work using its Zia assistant.

Here's a look at products.

Zoho Spend

  • The application has a dashboard that provides a consolidated view into procurement, accounts payable (AP), corporate travel, employee expenses and payroll.
  • Zoho Spend features procurement tools to simplify source-to-pay processes, onboard vendor onboarding and manage purchase requisitions and purchase orders and bills.
  • AP automation tools capture bills with OCR-scanning, matching and payment approvals.
  • A self-booking travel tools with integrations for corporate fares that are compliant with policies.
  • Tools to automate expense reporting.
  • Automated payroll processing with compliance across federal, state and local taxes.

Zoho Billing Enterprise Edition

  • The suite is designed to enable enterprises to monetize with multiple revenue strategies across 15 country-specific editions. Zoho Billing Enterprise Edition can help companies monetize via standard, project-based, subscription or usage-based billing.
  • Collection workflows are automated.
  • Lifecycle management tools are focused on subscriptions from trial to conversion to plan changes to retention.
  • Revenue recognition is built in with role-based dashboards and reporting.
  • Ask Zia is a finance assistant providing insights about billing efficiency and customer behavior.

Broad AI additions

  • Zoho added Co-Create Agent, which transparently creates invoices, quotes, credit notes, sales orders and custom reports.
  • Bank reconciliation with automated suggestions to categorize transactions.
  • Revenue forecasting via AI to predict trends.
  • Anomaly detection to flag inconsistencies with transactions.
Data to Decisions Future of Work Next-Generation Customer Experience Revenue & Growth Effectiveness New C-Suite Matrix Commerce Digital Safety, Privacy & Cybersecurity Innovation & Product-led Growth Tech Optimization zoho SaaS PaaS IaaS Cloud Digital Transformation Disruptive Technology Enterprise IT Enterprise Acceleration Enterprise Software Next Gen Apps IoT Blockchain CRM ERP CCaaS UCaaS Collaboration Enterprise Service Chief Financial Officer Chief Information Officer Chief Procurement Officer Chief Revenue Officer CPO CIO CTO Chief Technology Officer CISO Chief Information Security Officer CDO Chief Data Officer
Subscribe to