ServiceNow launches ServiceNow CRM: Aims to redefine category with platform, AI, workflows

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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ServiceNow unveiled ServiceNow CRM in a move that aims to expand its total addressable market, leverage its ability to automate workflows with AI and couple selling, servicing and marketing across multiple functional groups.

The launch of ServiceNow CRM, outlined at ServiceNow's Knowledge 2025 conference, was one of the most telegraphed launches ever. On the company's first quarter earnings call, CEO Bill McDermott made the company's CRM ambitions crystal clear. "There's not a day that passes when we don't hear from customers who are dissatisfied with their status quo," said McDermott. "For a long time, I've been saying no one has to lose for us to win. Our customers have now adjusted me. They want someone else to lose, so they can continue to invest more in ServiceNow."

Also: ServiceNow, UKG integrate AI agents across platforms

McDermott, speaking at ServiceNow Knowledge in a keynote, said that "AI is the absolute requirement for survival." "You've got to balance the audacity of the dream with new business models driven by AI so you grow for 10 years from now," said McDermott. "That's why we're going to bring AI agents to every corner of your business."

There's no need to name what vendors McDermott expects to lose in CRM, but you can connect the dots. It's obvious ServiceNow is going after Salesforce. ServiceNow is coupling lead and opportunity management, configure, price and quote, order management and fulfillment, customer service and support, field service and customer success and renewals. ServiceNow also can connect CRM across other functions, inventory and supply chain.

• ServiceNow makes its CRM ambitions crystal clear
• ServiceNow acquires Moveworks for $2.85 billion as it eyes CRM for agentic AI expansion
• Martin Schneider: ServiceNow’s Moveworks pickup and Agentic AI Push Solidify CRM Aspirations
• ServiceNow acquires Logik.ai, as it steps up CRM efforts
• Liz Miller: ServiceNow’s Logik.ai Pick Up Signals CPQ’s Shift to Experience
• ServiceNow acquires Cuein, aims to create AI agent feedback loop
• ServiceNow Yokohama release ups AI agent game

Amit Zavery, ServiceNow's Chief Product and Chief Operating Officer, said "let's face it, traditional CRM is broken. It is a patchwork of point solutions held together with duct tape and chewing gum. The result more complexity, more cost and less value."

In a briefing, ServiceNow CRM cited customers including Xerox, National Hockey League, Lumen and Kainos as well as Pure Storage. In the first quarter, ServiceNow said CRM is its fastest-growing workflow business.

The secret sauce for ServiceNow is its AI and workflow platform, which has expanded into multiple functions and use case from its IT service management days. By working horizontally across multiple data stores, ServiceNow's approach has been to connect systems, processes and workflows without needing you to move into one data store.

ServiceNow's CRM's pitch is relatively simple: Solve issues fast, adapt, run customer operations at half the cost and go live quickly. The approach is to service, sell and deliver on one platform that combines AI, data from multiple systems including inventory, contracts and operations and workflows.

ServiceNow said its CRM is aimed at a seamless experience that integrates processes and uses AI eliminate multiple screens, applications, spreadsheets and "human middleware." According to ServiceNow, CRM's limitation is that it is a system of record that ends at the front office. John Ball, ServiceNow EVP and GM of CRM and Industry Workflows, said ServiceNow can deliver "complete workflow automation from order capture through fulfillment, allowing customers to focus on value-added selling and delivering exceptional service to their own customers, not wasting time tangled up in out-of-date systems."

Differentiating with platform

ServiceNow's approach with CRM is enabled by a series of efforts outlined at Knowledge 2025 and put in place over the last two years.

The big message from Knowledge 2025 is that ServiceNow's Now Platform can be leveraged for any industry, any AI, data platform, workflow, cloud and system. Chief Innovation Officer, Dave Wright, said ServiceNow has the right to play in CRM because "we're the only company that unites AI, workflow and data on one enterprise platform."

"All our AI is delivered natively in every layer of the platform whether it's the UI, database, or automation layer, it's enterprise grade from day one," said Wright. "We can consume all the data that AI needs. We develop the workflow data fabric to be able to connect to all the data, to be able to unify it, and then be able to activate it."

This platform approach is also enabling AI agents and models on a broad level and combining to manage a digital workforce. Here’s a look.

AI Control Tower, which is a hub to govern, manage and secure any AI agent across IT, HR and CRM, model and workflow. The system covers multiple models from OpenAI, Google Gemini, Meta Llama and more, integration with AI systems from Google, Microsoft, LangChain and Amazon Bedrock. Key points about AI Control Tower include:

• Centralized monitoring of all AI systems (ServiceNow and third party).
• Ability to track AI asset adoption and usage.
• Risk and compliance.
• Value metrics to understand AI business impact.
• A single interface for different roles that oversee AI assets with data such as number of AI systems onboarded, deployment status, risk and compliance.

AI Agent Fabric, which connects agents across applications, provides interoperability and orchestrates agent workflows and data access on Now Platform and externally. Key features include:

• Dynamic layer so AI agents to communicate, coordinate and learn from each other.
• Coordinates ServiceNow and third party AI agents and external systems from the likes of Microsoft and others.
• Support for Model Context Protocol and agent-2-agent protocols and standardization of communication and partnerships with the likes of Box, Google Cloud and Microsoft.

AI Orchestrator, which was announced in January along with a broad partnership with Google Cloud. Features include:

• Ability to create teams of AI agents.
• Specialized agents across functions.
• Out of box agents for IT, CRM, HR and other enterprise workflows.

Those three capabilities, along with the data and workflow tools underneath, are powering CRM AI Agents, which are a suite of specialized agents that are designed to autonomously orchestrate and complete tasks from selling and fulfilling to servicing.

According to ServiceNow, its CRM AI Agents can do the following:

• Determine best course of action by resolving inquiries instantly, routing complex cases with full context, and managing workflows across departments.
• Start with conversational interactions to capture requests.
• Take that data and manage the fulfillment process and coordinate with humans when intervention needed.

The other enabling features behind CRM AI Agents is the broader platform as well as ServiceNow's efforts with its Workflow Data Fabric, announced in 2024. This data fabric was later enhanced with the Yokohama release. RaptorDB is also critical to the Workflow Data Fabric effort as well as connectors to multiple enterprise systems.

Zavery said the company is expanding its AI agent and workflow footprint due to its platform. He said:

"I'm here to show you exactly how we are delivering that platform to our customers and why we are different from all the AI pretenders out there. The reality is that today, AI is scattered across enterprises in silos, fragmented, disconnected, and to truly transform your business, we are bringing AI, data and workflows into the enterprise, enterprise grade platform you already rely on."

Zavery worked through AI agent orchestration, agent studio and connections to other agents from third parties via the AI Control Tower. "All others are building AI agents for their silos. Our AI agent orchestrator ensures the right agent handles the right task at the right time. It works behind the scenes, coordinating, resolving and accelerating work across the enterprise. It truly is AI intelligence built for scale," he said.  

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Cisco launches quantum lab, unveils quantum networking chip

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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Cisco is entering the quantum computing networking ring with a lab and prototype processor.

The move is notable since Cisco is a networking giant in the enterprise. In addition, quantum networking has been seen as a key piece of infrastructure. IonQ has highlighted the promise of quantum networking with acquisitions. However, it’s likely that your quantum vendors will be familiar since they are also in data centers.

• 2025 is the year of quantum computing (already)
• CxOs need to focus on quantum computing readiness, not the noise
• Quantum computing all in on hybrid HPC with classical computing
• IBM launches Flex Plan for quantum computing, aims to expand use cases

Cisco said its quantum networking chip prototype was developed with UC Santa Barbara and generates up to 1 million entangled photo pairs per second at room temperature. The chip also features telecom compatibility so may be of use to classical computing too.

Other things to note:

• The prototype has energy efficiency under 1mW.
• Fidelity up to 99%.
• The Cisco Quantum Lab will create networking components including quantum entanglement source chip and quantum switches with academic partners.

In a blog post, Vijoy Pandey, Senior Vice President, Outshift by Cisco, said quantum networking could accelerate quantum applications. He added that Cisco has more prototypes on deck including a distributed quantum computing compiler, Quantum Network Development Kit (QNDK) and Quantum Random Number Generator (QRNG).

"More components of our quantum data center infrastructure roadmap will be announced soon as we complete our vision of the quantum networking stack. In parallel, Cisco teams are implementing Post-Quantum Cryptography (PQC) NIST standards across our portfolio, ensuring classical networks remain secure in a post-quantum world," he said.

Pandey added that Cisco is looking to develop quantum networking for quantum computing as well as classical computing for immediate benefits. He also said that Cisco is building a vendor-agnostic framework to work with any technology. Quantum computing vendors range from approaches based on superconducting, ion trap and neutral atom approaches. "We don't need to pick winners among quantum computing platforms because we're building the networking fabric that will enable all of them to scale," said Pandey.

Constellation Research analyst Holger Mueller said:

"Cisco wants to be the network supplier in the quantum age beyond its mainstream networking technology. Cisco has developed networking technology that has to be quantum proof and safe and is now looking inside quantum machines. Cisco has its set of challenges, so it is a welcome change to see the network giant moving into new innovation fields."

Here's a look at Cisco's strategy.

Data to Decisions Innovation & Product-led Growth Tech Optimization Quantum Computing Chief Information Officer

Microsoft raises prices for Dynamics 365 Business Central

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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Microsoft said it is raising prices effective Oct. 1 for Dynamics 365 Business Central as it incorporates AI features into its platform.

The price increases, the first in five years, will hit smaller enterprises that typically rely on Microsoft Dynamics 365 Business Central.

Microsoft said Business Central now has Copilot and AI powered features for analytics, financials, account reconciliation, master data management and better interoperability with Microsoft Power Platform.

According to the company, Business Central will also have more storage per user license. Here's a look at the changes, priced in US dollars on a per user, per month basis unless otherwise noted.

Data to Decisions Future of Work Next-Generation Customer Experience Innovation & Product-led Growth Tech Optimization New C-Suite Marketing Transformation Digital Safety, Privacy & Cybersecurity Microsoft Chief Information Officer

IBM CEO Krishna: Now is the ROI stage of enterprise AI

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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IBM CEO Arvind Krishna said there is no law that enterprise AI has to be expensive, pegged to large language models and experimental.

In a keynote at Think 2025, Krishna outlined IBM's strategy and rollout of tools to build AI agents quickly and then orchestrate them.

"I think that the era of AI experimentation is over. Success is going to be defined by integration and business outcomes," said Krishna. "There is no law of computer science that says that AI must remain expensive and must remain large."

That theme played a big part of the news flow from Think 2025. At a high level:

• IBM's unified platform for building and managing AI agents, watsonx Orchestrate, will offer pre-built agents with use cases for industries with skills, integration and capabilities in HR, sales and procurement. There are also tools to build agents, orchestrate them and monitor and optimize with observability tools. Krishna said Watson Orchestrate Agent Builder can enable business users to build their own agent in 5 minutes.
• IBM launched next-generation Granite models. The company launched Granite 4.0 Mixture-of-Expert models and a new runtime engine.
• Watsonx.data will get new integration features to orchestrate data access and engineering in one interface and data governance software to curate, manage and use data.
• IBM announced GenAI Lakehouse to unify, prepare and govern structured and unstructured data for generative AI.
• The company launched IBM LinuxONE Emperor 5, IBM's next-gen Linux platform.
• A partnership with Lumen Technologies to bring IBM's portfolio of AI products and models to Lumen's Edge Cloud network.
• Expanded partnerships on AI agents with AWS, Oracle and Salesforce.

Krishna featured interviews with customers such as the Ferrari race team, Lumen and PepsiCo on managing data and AI agents.

• IBM launches Flex Plan for quantum computing, aims to expand use cases
• IBM maintains Q2 outlook, reports better-than-expected Q1
• IBM launches z17 mainframe, eyes AI workloads

For IBM, the company is trying to leverage horizontal and business expertise via its consulting unit and integration knowhow. Krishna is also talking business value given that projects are moving out of proof-of-concept mode.

Here’s a look at some of the key points from Krishna's keynote:

• "As I think about last year compared to this year, the one big difference is that AI has moved from experimentation to business value. What is the use case? How do I get my business to scale leveraging AI? We're thinking about ROI. We're thinking about business value," said Krishna.
• Success is defined by integration, intelligence and automation in enterprise workflows. AI is an accelerant, said Krishna.
• Smaller, special purpose models will be critical to drive more cost effective AI, he said.
• "IBM is incredibly focused on enterprise AI. We do not focus at all on consumer AI, and that is why you see our focus on purpose built models, cost, effectiveness, sovereignty, and security. How do we make and decrease the cost of enabling AI inside the enterprise?" said Krishna.
• Speed of inference will depend on hybrid infrastructure that brings data closer to the edge.
• "Quantum is no longer science fiction. It's now in the realm of engineering. And when you're in the realm of engineering, the question becomes, how do you get that next step? And then these systems are going to be at a scale that is going to be truly remarkable and truly surprising. We are building these full stack quantum systems," said Krishna.

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Palantir Q1 commercial momentum continues to run, ups 2025 outlook

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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Palantir continues to land US commercial accounts as it raised its outlook for the second quarter and 2025.

The company reported first quarter non-GAAP earnings of 13 cents a share on revenue of $883.86 million, up 39% from a year ago. GAAP earnings for the first quarter were 8 cents a share. Wall Street was expecting Palantir to report first quarter earnings of 13 cents a share on revenue of $862.13 million.

Palantir CEO Alex Karp said the company is projecting 2025 US commercial revenue growth of 68% and total revenue growth of 36%. Karp said, "we are delivering the operating system for the modern enterprise in the era of AI" and there is a "a tectonic shift in the adoption of our software."

Recent:

• Databricks, Palantir forge integration pact
• Palantir CTO: Engineering on DeepSeek 'is exquisite'
• Palantir US enterprise demand surges as Q4, 2025 outlook strong

On a Rule of 40 score basis, Palantir scored 83% in the first quarter. Rule of 40 is a SaaS financial metric that dictates a healthy SaaS company should have a combined growth rate and profit margin of 40% or more.

As for the outlook, Palantir projected second quarter revenue between $934 million to $938 million with adjusted income from operations between $401 million and $405 million. For 2025, Palantir projected revenue of $3.89 billion to $3.902 billion with adjusted income from operations between $1.711 billion to $1.723 billion.

The numbers for the first quarter were impressive.

• US revenue was up 55% in the first quarter compared to a year ago to $628 million.
• US commercial revenue was up 71% to $255 million. US government revenue was up 45% to $373 million.
• The company closed 139 deals of at least $1 million, 51 deals of at least $5 million and 31 deals of at least $10 million.

In his shareholder letter Karp noted the following:

• Management: "This breed of company will never spring from the mind of a committee; it would never have been permitted to endure in its current form, with thousands of employees organizing themselves around problems at hand, if we had submitted to the conventional managerial model in American corporate life."
• US government spending: "Our software systems for planning and executing special forces and other military operations, and for assessing and selecting targets, has been embraced by the American defense sector."
• AI and LLMs: "The rush towards large language models, as well as the foundational software architecture that is capable of making them valuable to large organizations, has turned into a stampede. What was once a relatively orderly process of assessment and evaluation of these novel technologies has evolved into a ravenous whirlwind of adoption as an increasing number of institutions grasp the magnitude of the shift that is washing over industry and government."

 

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AWS preps healthcare, life sciences AI agent with Wiley content

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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Amazon Web Services will launch an AI agent for scientific literature via a partnership with Wiley, a publisher of journals.

The announcement will be made at the AWS Life Sciences Symposium in New York on Tuesday. The AWS conference will feature a bevy of big name customers including Merck, AstraZeneca, Genentech, Pfizer and Johnson & Johnson.

AWS has been developing a horizontal approach to AI agents via Amazon Q, which has gained momentum and a story after re:Invent 2024. The collaboration with Wiley highlights how AWS wants to also take AI agents into various industries.

According to Wiley, the literature search agent is available as part of an AWS open source toolkit for healthcare and life sciences agents. AWS' toolkit has a catalog of starter agents and frameworks for building and orchestrating them. Use cases include biomarker discovery, clinical trial protocol generation and detailed content searches.

Here's a look at a sample agent for healthcare and life sciences from AWS.

Wiley and AWS said that full-text content from the publisher can be integrated into AWS' agent stack including Bedrock Agents.

More on AI agents:

• Agentic AI: Everything that’s still missing to scale
• BT150 zeitgeist: Agentic AI has to be more than an 'API wearing an agent t-shirt'

More on healthcare:

• AI agents aimed at healthcare, but data interoperability still a big issue
• How GE Healthcare is approaching generative AI, LLMs, and transformation
• BT150 Spotlight: Centurion Health's Johnny Wu on delivering healthcare in prisons
• BT150 Spotlight: MultiCare Health System's Laurie Wheeler on optimization, change management and healthcare transformation
• BioNtech, InstaDeep bet on genAI models to advance R&D, drug discovery, cancer treatment
• AI 15O's Matt Lewis on GenAI adoption, psychology and life sciences
• Welldoc Chief AI Officer Anand Iyer on AI, data and healthcare transformation
• How ResMed’s data prowess sets it up for AI, sleep health market expansion

Data to Decisions Next-Generation Customer Experience Future of Work Innovation & Product-led Growth Tech Optimization AR Chief Information Officer

IBM launches Flex Plan for quantum computing, aims to expand use cases

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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IBM launched a Flex Plan for access to its quantum computing hardware in a move that aims to expand access for organizations, enterprises and researchers who want access without monthly limits.

The IBM Quantum Flex Plan provides access on day one with an entry point of $30,000+ to gain access to Big Blue's entire fleet of quantum systems. Flex plan users will also get the advanced software features, support and early access to new releases.

According to IBM, the Quantum Flex Plan is aimed at research and development teams that need quantum systems on a project basis that's less predictable. Examples of project based access would be times of peak research cycles or preparing a conference submission. IBM recently upgraded its Quantum Data Center to its latest Heron quantum processor.

2025 is the year of quantum computing (already) | CxOs need to focus on quantum computing readiness, not the noise

Constellation Research analyst Holger Mueller said:

"In a sign that technology is no longer the No. 1 challenge for the quantum industry, IBM is introducing a more flexible, lower priced system, that should make the  first trials and evaluation of quantum technology easier in 2025. It is also a sign that IBM has the capacity to offer this flexible pricing. Few quantum players have capacity."

Academics and startups would also be examples of users that would explore quantum use cases without committing to a long-term plan. For instance, an academic researcher could use the Flex Plan to match funding levels and educators could use Flex to teach quantum computing.

• Constellation ShortList™ Quantum Full Stack Players
• Constellation ShortList™ Quantum Computing Platforms

IBM noted that its flex plan fills a gap above the free Open Plan and pay-as-you-go offerings. IBM also offers a Premium Plan, a subscription that is designed for customers that want a longer commitment and access to quantum systems.

Key points about IBM's Quantum Flex Plan:

• The Flex Plan is designed for compute-intensive quantum workloads on a per-project basis.
• The structure is pre-purchased minutes with no monthly caps.
• Flex plan addresses cases that require bursts of sustained executions such as chemistry, machine learning and optimization.

 

IBM Quantum:

 

• IBM upgrades IBM Quantum Data Center with Heron
• IBM launches Qiskit services for quantum computing
• When Quantum SDKs Go to the Gym, Qiskit Wins
• IBM Boosts the Software Side of Quantum

Data to Decisions Innovation & Product-led Growth Tech Optimization Quantum Computing Chief Information Officer

Resilience is the key enterprise theme and it favors the large

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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Resilience is the major theme as enterprises report quarterly results and the biggest takeaway is that the giants will weather the storm and smaller companies won’t.

In call after call, technology, business model and supply chain resilience are major topics. Even the large companies that are out of position--say PepsiCo compared to Coca Cola--will figure out an uncertain economy, tariffs and plunging consumer confidence. Apollo has a good deck of the most recent indicators and why CEOs are talking about resiliency so much.

It's time you start thinking about the various forms of resiliency and how they apply to your enterprise.

Consider Walmart's approach to its platform, digital flywheel and optimized scale. Consider the financial giants that continually invest in AI. Consider Google, which is exposed to advertising but has the scale to weather storms, and how it has multiple levers. The list goes on.

Here's what Coca Cola CEO James Quincy said on the company's first quarter earnings call and its supply chain that may actually be tariff proof.

"We're ironically known for Coca-Cola, the world's most global brand and a set of other global brands. But actually it's a very profoundly local business. The beverages in each country are largely made in that country by local employees using local inputs."

Coca Cola in the US system is nearly self-contained. Ditto in Brazil and most regions around the world.

"The imperative is to make the global brands locally relevant. And in the moments of geopolitical tension, one of the key strategies is to drive and reinforce the made in or made by. The fact that it's a local business, the factory is down the road from you, your neighbors make the product. And this underlining of the localness of the production and the distribution and the workforce plus reinforcing affordability tends to be the key thing to do, particularly with Brand Coca-Cola in these moments," said Quincy. "It's not the first time it's had to be used. I'm sure it won't be the last. And so, we think our business model is set up for an environment that can take a degree of disturbance because it's a very resilient business model."

Turns out the Coca Cola model will have to be replicated by most enterprises. The big question is how fast companies can pivot. It's not like Apple can move its manufacturing out of China overnight.

• Microsoft expands at Coca-Cola as part of multi-cloud strategy that includes AWS

As a result, many companies are pulling their outlooks.

What remains to be seen is how resilient smaller enterprises can be in a shaky economic environment. UPS CEO Carol Tome, who leads a company that is revamping its network and laying off workers, said small businesses are in trouble.

"Many of our SMBs are 100% single-sourced from China. And this is causing so much uncertainty in the marketplace because the administration has announced, as 145% tariff on China goods starting May 2, and the elimination of the de minimis exception," said Tome. "Our SMBs, who don't have the working capital capabilities to pull forward inventory, are saying, Wow! how are we going to handle this cost increase that's coming our way. It doesn't mean that they're not trying to look for alternate forms of supply. They're working with original equipment manufacturers, trying to move to other countries, but as you can appreciate, the large companies get to take the first phone call and they're the ones that are willing to work on changing supply chain."

Those scenes from the buy side are worth pondering as you survey the tech vendor landscape. The upshot: The tech vendors that can save you money will do well. The big legacy types that are adept at squeezing you more are likely to be disrupted.

ServiceNow CFO Gina Mastantuono said the company went through "a very rigorous analysis of our business and its exposure to areas that could potentially be impacted by the current geopolitical."

She added: "What I'll tell you is that demand remains strong. The customers we're talking to are absolutely focused on the future and growth in and cost out. ServiceNow platform remains a deflationary tool that customers are leaning into in times of uncertainty."

ServiceNow is hellbent on growing its CRM business at the expense of Salesforce.

Now let's connect a few other dots. Freshworks is focused on competing with ServiceNow in the midmarket. "Midmarket companies need to automate their IT department, but a ServiceNow implementation is too heavy and expensive," said Freshworks CEO Dennis Woodside.

You can map your entire stack and find similar connections. There are vendors that will enable exponential efficiency and those that will be a drag. Know the difference.

Data to Decisions Next-Generation Customer Experience Tech Optimization Future of Work Innovation & Product-led Growth New C-Suite Supply Chain Automation Cloud Digital Transformation Disruptive Technology Enterprise IT Enterprise Acceleration Enterprise Software IoT Blockchain ERP Leadership Collaboration M&A Chief Information Officer Chief Supply Chain Officer

OpenAI delivers postmortem on GPT-4o's sycophancy

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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A large language model's behavior issues and personality quirks should be tested as any safety risk would, according to OpenAI's postmortem after an update to ChatGPT-4o made the model sycophantic.

In a postmortem, OpenAI detailed what went wrong with the GPT-4o update, why the model was rolled back and what the company is doing to prevent personality issues in the future.

Here's the short version: OpenAI launched the update to GPT-4o and real-world interactions quickly revealed the models was a sycophant. It didn't take long until users noted that GPT-4o suddenly went over-the-top with the flattery, which was obviously insincere (as if a model could be sincere).

The postmortem on the GPT-4o rollout reads like an outage report. OpenAI's take is also instructive as model creators aim to put more personality and emotional intelligence into models.

Going forward, OpenAI said it will treat model behavior issues as launch blocking as it would other safety risks. OpenAI noted that its testing on general model behavior "has been less robust and formalized relative to areas of currently tracked safety risks."

OpenAI also said that it needs to better measure signals on model behavior and acknowledged that it won't predict every issue. The other takeaway from OpenAI is that there is no small launch.

In its blog post on the issue, OpenAI said:

"One of the biggest lessons is fully recognizing how people have started to use ChatGPT for deeply personal advice—something we didn’t see as much even a year ago. At the time, this wasn’t a primary focus, but as AI and society have co-evolved, it’s become clear that we need to treat this use case with great care. It’s now going to be a more meaningful part of our safety work. With so many people depending on a single system for guidance, we have a responsibility to adjust accordingly."

OpenAI said it has been updating GPT-4o to make it more helpful and personable. It's part of an effort to give LLMs more emotional intelligence. It has been clear for the last year that frontier models each have their own personalities. OpenAI botched the reward signals that kept GPT-4o's sycophancy in check. The solution was to roll back the model, a chore that took 24 hours.

The OpenAI post is worth a read because it highlights a few key items or me:

• LLM personalities matter.
• Model behavior is essentially the new UI and the thing that's likely to be sticky over time. After all, you're more likely to stick with a model you actually like personally.
• Qualitative features may be the most important with LLMs. Does the average bear really notice if one model has a math score 1% better than another. Ditto for code or half the other metrics that are benchmarked.
• Emotional intelligence in models (faked just like humans do) is a key feature, but can go horribly wrong.
• LLMs are simply software and the personification of them is likely to lead to more issues like this OpenAI rollback.
• Credit OpenAI for the transparency.

Data to Decisions Chief Information Officer