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Hot Take: Oracle Brings More AI to the Table for Revenue Teams

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

Oracle made some significant announcements around its continuing generative and agentic AI strategy today at CloudWorld in Dubai. The new additions to the Oracle Fusion Cloud Sales portfolio includes new out of the box AI agents - aimed at streamlining key sales and CX processes to driver productivity and improve customer relationships. 

The new AI gents include:

  • Customer engagement agent: Helps sales teams save time and improve productivity by streamlining customer communication. For example, the agent can quickly generate customer-ready emails designed to bypass spam filters, while also enabling sales representatives to adjust the tone and call-to-action for their specific audience.
  • Customer records agent: Helps sales teams more efficiently maintain up-to-date account activity records. For example, the AI agent can summarize recent account activity, organize meeting notes, and automatically input them into the system for internal team access and collaboration. To meet the needs of different sales teams, the agent can also proofread and reformat meeting notes, such as incorporating bullet points or action items. 
  • Customer intelligence assistant: Helps sales teams quickly get up to speed on accounts and develop more meaningful customer connections. For example, the generative AI-powered assistant can quickly produce a summary of the account, including recent activity, current sentiment, and contract status, by leveraging end-to-end data from sales, finance, and supply chain to deliver a more holistic, personalized, and contextually relevant account overview.
  • Multilingual support: Helps sales teams seamlessly connect with global audiences. For example, embedded generative AI capabilities help sales teams to quickly translate customer engagements and interact with customers in other languages.

The agent additions bolster an already solid list of AI-powered features across the Fusion application portfolio. And these new agents seem to be smart additions as well - driving seller productivity by reducing manual, common tasks - giving time back to sellers to focus on the human element of building strong customer relationships. 

Oracle is unique in that the company has continued to deliver on a previous promise that it sees AI as just another component of building a strong CX product set. And therefore, its AI features and capabilities are not priced separately but rather included in the base fee for Fusion Sales, in this instance. Compare this to companies like Salesforce, where its Agentforce offering is adding signifiant additional costs to users, and Oracle is building a compelling case for itself as a viable CX alternative in the enterprise even outside of its solid install base. 

Oracle says that owning so much of its own infrastructure to deliver at via Oracle Cloud Infrastructure and other data and security elements allows it to keep its own costs low and thus extend the savings to users. Also, the company notes that Oracle customers tend to be achieving fast time to value with their AI tools because so much of the data, application layer, security, etc. is pre-integrated - meaning more federated data for more effective AI results, all in a more secure and guardrailed environment. 

"Sales processes have become overcomplicated and with so many administrative and complex tasks required, sales teams are struggling to find the time needed for effective and meaningful customer communication,” said Rob Tarkoff, executive vice president and general manager, Oracle Cloud CX. Said in a company statement “The new AI agents and generative AI capabilities within Oracle Cloud Sales eliminate many of these rigid and time-consuming tasks, which enables sales teams to boost productivity and create more impactful connections with customers.”

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Delta Air Lines completes cloud migration with focus on AI and data-driven customer experience

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

Delta Air Lines has migrated most of its technology infrastructure to the cloud and is starting to leverage generative AI (GenAI) for personalized pricing, digital concierge services, and optimizing the customer experience.

The 100-year-old airline recently outlined its technology investment at its Investor Day in November, then announced partnerships and various initiatives at CES 2025 and followed up with strong fourth-quarter earnings and a bright outlook.

Get this customer story as a PDF

Delta reported 2024 earnings of $3.46 billion with revenue of $61.6 billion, up from $58 billion in 2023. For 2025, Delta projected earnings growth of more than 10% with first-quarter revenue growth of 7% to 9%. For 2025, Delta expects free cash flow above $4 billion.

Speaking at CES 2025, Delta CEO Ed Bastian outlined Delta Concierge, which is a GenAI tool designed to personalize customer experience within the Delta app. Delta also announced partnerships with Uber, Joby (an electric air taxi service), and a partnership with YouTube.

“Together, these products and partnerships reflect our continued commitment to investing in and providing our customers with a superior travel experience,” Bastian said. “They drive greater engagement with our SkyMiles members that extend well beyond air travel, improving customer satisfaction and deepening loyalty to Delta.”

Indeed, Delta, which has sparred with CrowdStrike over the security vendor’s outage, is playing the long game with customers and is betting a more agile technology infrastructure and AI can create the personalization needed to drive lifetime value of a flier.

The airline has been investing in technology for the last three to four years. In 2022, Delta said it would migrate its infrastructure to AWS. That work is mostly complete, Bastian said, speaking during Delta’s Investor Day.

“We made some pretty healthy investments over the course of COVID to move the majority of our technology infrastructure to the cloud with AWS,” Bastian said. “And we’re just about at the end of that journey. It’s going to drive a lot of agility that’s going to drive a lot of speed, a lot of efficiency, for our ability to continue to not just provide stability to our infrastructure, but it’s also going to allow us to continue to change and move faster than others. Our platforms are modernized. Our software is continuing to get better, and it’s also allowed for the integration of many of the new AI and data analytics tools that you hear a lot about.”

Bastian said that Delta has invested about $500 million over the last three to four years moving to AWS. But that investment will pay off because it’ll enable Delta to leverage AI.

“We all know there’s a lot of hype around AI, and it’s something that we all look at and wonder if it’s going to live up to the promise,” Bastian said. “I think AI is going to be incredible in terms of its impact on our business, but it’s only going to be incredible if we’re prepared to actually harness the power. Our focus on AI is to learn, and to listen, and to make certain that we’re ready before we jump in with both feet.”

Delta is looking to apply AI to three core areas of its business. These include:

Reliability of operations. “You think about the 5,000 flights a day that operate in all kinds of weather conditions, with all kinds of variables, with staffing coming from all over the world—it’s a Rubik’s Cube every single day, and you’re trying to optimize and get the best answer,” Bastian said.

Bastian added that scheduling, prioritization, and more-efficient routing will all be key use cases for AI.

Connected experiences. Bastian said that Delta is going to leverage technology to connect with customers. At AWS re:Invent 2023, Delta said that it leveraged Amazon Bedrock to try out different models to deliver answers to customers. It’s very early, but Delta is able to hit you up during a log-in and know it’s your birthday. The free Wi-Fi and seamless log-in experience doesn’t hurt, either.

Revenue growth. Delta will leverage AI to drive pricing and revenue growth. “When you have a brand that has a 26-plus-point advantage versus your network competitors but your revenue premium is 14 points, I think there might be opportunity to do better,” Bastian said.

The framework for AI

Bastian said that Delta is early in its AI journey, but it has a framework for projects over the next three to five years. The framework is simple: Every AI project needs to fit into one of Delta’s three core priorities of reliability, experience, and revenue generation.

Delta’s operating margins are typically between 11% to 12% and the company expects those margins to grow to the mid-teens in the years ahead. Delta is also planning to grow earnings at a double-digit clip on average over the next five years.

Glen Hauenstein, President of Delta, is on the hook for delivering those metrics and said technology is critical to delivering a premium product and experience. “We saw this many years ago and went on a journey to de-commoditize the airline space,” Hauenstein said.

Hauenstein noted that everything Delta does revolves around the brand: The investment in airport facilities is brand. The network of lounges is brand. Technology partnerships is brand. The ability to expand into adjacent travel categories is brand. And the membership experience is brand.

“We’re able to describe an experience and not only create it, but sell it and retail it,” Hauenstein said. “Retail is really the frontier that we will continue to lead over the next three to five years.”

Delta also plans to use technology to segment its audience. Delta has strong ratings with millennials and baby boomers, two generations with money for travel, and is installing a digital footprint that can grow its share for future generations.

Going forward, Delta will optimize its offering through data and technology. The data will lead to experimentation, new bundles, and subcategories for seating. “We’re going to test and learn along the way, but we’re going to start from the bottom up,” Hauenstein said. “In 2025, we’re going to try some segmenting, some additional segmenting of the main cabin. You’ll see us attempting and really testing what consumers want in their bundles and what they’re willing to pay for. That’s really the way I think good retailers work and we’re going to transform ourselves over the next three to five years.”

‘Right offer, right time, and right channel’

When you listen to Bastian and Hauenstein riff, they do sound more like omnichannel retailers than an airline.

And like most omnichannel retailers, Delta will be betting on data to connect with customers.

Hauenstein said Delta is looking to connect the “right offer, right time, and right channel.”

“What we’re really trying to do is to get inside the mind of our consumer and present them something that’s relevant to them at the right time with the right price,” Hauenstein said.

Delta has partnered with an Israeli startup called Fetcherr, which uses GenAI to create optimized offers. Hauenstein said Delta has worked with Fetcherr for more than a year and about 1% of the network is being priced by the startup.

“This is a full re-engineering of how we price and how we will be pricing in the future. And if you think about it today, there are two disciplines: There is pricing, which sets the price points, and then there’s revenue management, which controls access into the inventory of those price points,” Hauenstein said, noting that over time pricing and revenue management will converge. “It’s going to really be just offer management. We will have a price that’s available on that flight, on that time to you, the individual.”

With the help of AI, Delta is betting that its systems can act like a digital analyst that can simulate real-time price points and demand.

“We’re letting the machine go ahead and price in a very controlled environment,” Hauenstein said. “It’s going to be a multiyear, multistep process as we continue to learn, innovate, teach the machine and change the business process, but the initial results show amazingly favorable unit revenues.”

Delta executives said the company will go slow even though it wants first-mover advantage and to retool its business processes as quickly as possible. Hauenstein said Delta will iterate to offer “clean choices” that aren’t overwhelming when it comes to multiple offers.

“Personalized and seamless experiences—we put a lot of effort into this, and we have a long way to go,” Hauenstein said, adding that these experiences will be priority now that the cloud migration is complete. “We can redirect to really implementing some of these changes that we have in the queue that have been kind of sitting, waiting for the cloud to be fully migrated.”

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Monday's Musings: Exponential Efficiency In The Age Of AI At Davos

Media Name: @rwang0 @davos @wef #WEF25 #Davos Town.jpg
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

AI Will Dominate The Davos Agenda, Yet Only A Privileged Few Can Pay For It

While, Trump, China, and the global economy take centerstage at this year’s World Economic Forum, AI will be the main topic du jour. Senior executives and policy wonks seek to understand how AI will transform businesses, societies, and economies. The AI Age truly is the 4th Industrial Revolution, not the other stuff that was peddled as conference fodder over the past five years in Davos (see Figure 1).

Figure 1. Welcome To The AI Era

Unlike the Internet Age, where there was a push for massive decentralization, open systems, many players, and lower costs, the AI Age has so far become the opposite (see Figure 2).

Figure 2. AI Age Is Opposite of Internet Age

 

 

Today, the AI systems are highly centralized, closed, with fewer players, and much higher costs. In fact, the barriers of entry to AI will create an AI divide bigger than the current digital divide. Many countries will not be able to afford the compute power, the energy, and the human power required to effectively manage AI. And even worse, the world is abuzz about AI, yet the costs of AI continue to go up, not down. Constellation Research expects an AI divide worse than than today’s digital divide.

Legacy Costs And Technical Debt Burden Most Organizations

Concurrently, the legacy costs of the Internet Era and technical debt continue to pile up with hybrid cloud, legacy transactional systems, expensive and dated software, and rising maintenance costs by technology vendors trying to raise account values not commensurate with the increase in innovation. HINT: most organizations are paying too much for technology without a proper return.

One favorite quote from a Constellation’s Executive Network (CEN) member:

"As a CFO, all my costs go down with volume and time, except for F!@#%G healthcare and tech (SaaS)."

This CFO’s astute comments reflect the current malaise in the SaaS world and cost of hyperscaler compute with lift and shift. In fact, today’s cost structures are way too high and organizations will continue to struggle to cut costs from the Internet Era to pay for the AI Era. The AI era has yet to show that the investments will yield productivity gains for many. Hence the push for exponential efficiency to pay for AI and other innovations.

Exponential Efficiency Explained

Exponential efficiency refers to an algorithm or function whose running time grows exponentially with respect to its input size. In other words, as the input gets larger, this type of algorithm experiences rapid growth in its execution time.

 

The simple rule for exponential efficiency in the first order: 10 X better or 1/10th the cost.

In the second order of exponential efficiency, organizations achieve: 10x better AND 1/10th the cost.

This continues as organizations achieve the holy trifecta of faster, better, AND cheaper. Yes, all three can be achieved when exponential efficiency is applied. Now, many readers may contemplate whether this is possible or not. Recently both X (formerly Twitter) and Meta (formerly Meta), found ways to cut their engineering teams with both AI and automation to achieve exponential efficiency. X reduced 2/3’s of engineering staff and others with little detriment. Meta continues to reduce 1/3 or more of its engineering teams and others with very little detriment. In fact, in back office financial operations, they may be able to get to 50% automation in the next two years.

Exponential Efficiency Will Help Pay For AI

 

More than just paying for the high cost of AI, organizations see the potential but need to fund innovation with cost savings. Today’s cost structures are no longer sustainable for the AI era. Legacy infrastructure costs must be taken down by 1/10th or improvements must be 10 times better in order to achieve exponential efficiency. In the Internet Era, telecommunications, commerce, distribution, and financial services costs were exponentially cut to make way for this new transformational technology. These innovations paved the way for 1000’s of new business models and monetization techniques leading to explosive growth and societal advancement. In almost every industry, the dawn of exponential efficiency has arrived, yet legacy players struggle to grasp the impacts. Here are five industries where exponential efficiency has arrived:

  1. Financial services. SWIFT wires run about $25 a transaction. ACH costs about $2.50 per payment. ATM costs run about $1.000. In India, the government set up a payment system for over 1 billion people that costs next to free. Why does a Mastercard or Visa or Amex payment gateway exist? These merchant and user fees have been disrupted and smart enterprises will stop paying soon.
     
  2. Defense and military. Expensive weapons programs create million dollar missiles to be used on the battlefield. Meanwhile, $100 drones have better effectivity. This consumerization of dual use technologies will continue with robotics as future kinetic wars may not be fought with human combatants. The gorgeous drone shows on display will be AI controlled dual use for warfare.
     
  3. Enterprise software. Users locked into legacy systems pay $500 to $1000 per user per month for CRM, ERP, collaboration, office productivity, video conferencing etc. an Indian software pioneer, Zoho, offers all this for $10 per user per month. The cloud vendors who were the young Turks challenging legacy vendors are now the ones holding customers hostage and hindering innovation. The cycle has been repeated with a lot of money wasted for slow innovation and very little return to enterprises.
     
  4. Energy and utilities. The cost of electricity continues to go up, while the raw carbon used to power is lower in cost when adjusted for inflation. Why? The cost of pensions and capital expense of power plants and transmission continue to rise. Many localities pay up to $0.25/kwh for not just transmission, but generation. In less than a decade, China will be able to produce energy at close to zero with hydro, nuclear, and battery storage from solar. Nuclear costs China $.05 per kw/hour. Any country who succeeds at lowering power costs will dominate economies with lower cost manufacturing, compute, and AI.
     
  5. Public sector. The US will begin an exercise to take the bloat out of government. The Department of Government Efficiency (not an official department) will be focused on fraud, waste, abuse, and efficiency. With some of the best minds, this effort could create an efficiency in public sector that would have ripple effects throughout the economy and free up funds for more quality of life spending for society. This advantage will give the US another advantage on the world stage beyond digitization.

Senior executives must prepare for a swath of new competitors to create exponential efficiency disruption. For example, in the consulting industry, the combination of automation and AI, a glut of young computer science graduates and the carnage of layoffs for older workers will open the opportunity for new firms built on AI to operate with 1/10th the labor. Expect the first $1 billion consulting firm to achieve a revenue per employee of $10 million - $25 million each in the next five years.

The Bottom Line: Put AI To Work On Exponential Efficiency

At the 2024 Constellation Connected Enterprise executive summit at the Ritz Carlton Half Moon Bay, exponential efficiency pioneer David Giambruno showed how he achieved $712 million in hard costs with five different industries. David used a combination of AI and automation with bare metal cloud compute to deliver a 68% reduction in IT costs in 21 months. His teams were able to rewrite legacy code and reduce overall cloud costs with this novel approach.

Time is of the essence. Exponential efficiency funds the AI projects which set up the foundation for organizations achieving Second Order exponential efficiency gains. PE firms looking at turnaround playbooks will start with a thesis on exponential efficiency before starting the turnaround. Investment bankers will roll out their exponential efficiency playbooks for post-merger integration models. Be warned. Any Global 2000 company missing the exponential efficiency playbook will be left behind without the resources to fund their AI investments.

Your POV

How will you achieve exponential efficiency? Will you aim for 10x or 1/10th?

Add your comments to the blog or reach me via email: R (at) ConstellationR (dot) com or R (at) SoftwareInsider (dot) org. Please let us know if you need help with your strategy efforts. Here’s how we can assist:

  • Developing your metaverse and digital business strategy
  • Connecting with other pioneers
  • Sharing best practices
  • Vendor selection
  • Implementation partner selection
  • Providing contract negotiations and software licensing support
  • Demystifying software licensing

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Although we work closely with many mega software vendors, we want you to trust us. For the full disclosure policy,stay tuned for the full client list on the Constellation Research website. * Not responsible for any factual errors or omissions.  However, happy to correct any errors upon email receipt.

Constellation Research recommends that readers consult a stock professional for their investment guidance. Investors should understand the potential conflicts of interest analysts might face. Constellation does not underwrite or own the securities of the companies the analysts cover. Analysts themselves sometimes own stocks in the companies they cover—either directly or indirectly, such as through employee stock-purchase pools in which they and their colleagues participate. As a general matter, investors should not rely solely on an analyst’s recommendation when deciding whether to buy, hold, or sell a stock. Instead, they should also do their own research—such as reading the prospectus for new companies or for public companies, the quarterly and annual reports filed with the SEC—to confirm whether a particular investment is appropriate for them in light of their individual financial circumstances.

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HOT TAKE: ServiceNow Hits the Gas on Agentic AI Roadmap with Cuein AI Pick Up

Liz Miller
Vice President & Principal Analyst Constellation Research
About Liz Miller: Liz Miller is Vice President and Principal Analyst at Constellation, focused on the org-wide team sport known as customer experience. While covering CX as an enterprise strategy, Miller spends time zeroing in on the functional demands of Marketing and Service and the evolving role&nbsp;of the&nbsp;Chief Marketing Officer, the rise of the Chief Experience Officer, the evolution of customer engagement and the rising requirement for a new security posture that accounts for the threat to brand trust in this age of AI. &nbsp;With over 30 years of marketing, Miller offers strategic&nbsp;guidance on the leadership, business transformation and technology requirements to deliver on&nbsp;today’s CX strategies. She has worked with global&nbsp;marketing organizations to transform… Read more

What happens when the “Platform of Platforms” goes deep into conversations between agents and customers or employees? For ServiceNow the hope is to radically accelerate AI agents’ capacity to comprehend in meaningful ways and perhaps, find new ways to initiate, optimize and even correct workflows that happen as a result to knowing just a little bit more than the other guys. To read the press release and Insights coverage.

What we know about the deal: ServiceNow has signed an agreement to acquire Belmont, CA based conversational intelligence firm, Cuein AI. Freshly dubbed a “conversation data and analysis platform” those of us in the service space will recognize the solution's capacity to ingest, analyze and action on customer conversations across a broad range of platforms, including interactions with chatbots and Interactive Virtual Assistants (IVA). While no financial terms were disclosed in the announcement, we do know that the company’s primary investors were Lightspeed Venture Partners, Khosla Ventures and Webb Investment Network…with additional investment by ServiceNow and Salesforce...so it shouldn't go unnoticed that ServiceNow may have beaten Salesforce to this punch.

What makes Cuein AI so interesting: What started as an AI tool to unlock the sentiment, intelligence and actionable real-time moves organizations could be making thanks to chat transcripts and data has turned into a more comprehensive conversation analysis solution. While Cuein absolutely mines chatbot engagements for actionable cues and signals from customer interactions with agents, it has taken analytics farther by looking beyond the lagging indicators of experience like the post engagement survey and set AI to work to infer customer satisfaction measures and foster action and change. For contact center customers, Cuein holds the promise that customer conversations in any channel, including voice, can be more than just ingested and analyzed for post-mortem understanding. Their voice analytics visualizes the flow of conversation and identifies real time trends, patterns and proactively alerts when those patterns are actually problems. But beyond the contact center or service environment, Cuein could be a very interesting optimization superpower for ServiceNow and their AI agents.

For Service and Experience Leaders: While Cuein has been on the radar—not to ruin the surprise, but they were included in the consideration group of 20+ stand alone offerings for an upcoming new shortlist focused on Conversational Intelligence in Customer Service—with integrations with CCaaS and CRM solutions like 8x8, Genesys, Microsoft, NICE, Salesforce and Zendesk along with LLM and model companies like OpenAI, Cognigy and Amelia, they were an emerging conversation and not quite yet a household name. ServiceNow did not include any statement of intention for what will happen to Cuein and if existing customers like Anthropologie, Crocs or Voya Financial would continue leveraging the solution outside of a ServiceNow environment. So…for existing customers...stay tuned is the message here. However, if you are a ServiceNow customer, now is the time to start thinking about which part of your workflows, your applications and your AI-powered bots could benefit from some self-awareness and self-healing. Where Cuein shines is in the ability to identify breakdowns and bottlenecks in conversations, providing much needed understanding into everything from how a bot is addressing customer needs to how product could be improved. Appropriately applied, Cuein should be using conversation for intelligence as opposed to a solution that is really narrowly focused on intelligence from conversations. And yes, it’s a nuance, but it is an important mindset shift. Intelligence from conversations only improves future performance of a bot or an agent. Conversations for intelligence turns conversations between any two points including between customers and bots, customers and agents, or agents and bots and turns it into a treasure trove of data which not only turns into enterprise-wide intelligence but also becomes a closed loop of knowledge to optimize conversations in-flight.

For AI, IT, Digital and Transformation Leaders: Cuein is about more about continuous improvement than it is about a tool for a specific function. In an age when agentic AI is being infused in almost every process and every interface in the enterprise, mining for patterns, flows, breaks and failures should be one of those ambient processes focused on improvement and optimization rather than reporting and post mortems. When a bot is delivering less than optimal results. In study after study, customers are admitting that there is far less leeway for agentic or bot-based failed experiences. After a bot fails to resolve and issue or provide contextually accurate and valued outcomes, a customer will not use that technology again and will double-down on the demand for a live-agent experience. Bottom line: bots have one shot where humans would typically get another chance. This is where AI intelligence data comes into play to diagnose, alert, prompt or even provide recommended fixes to ensure that design and optimization is fluid and continuous.

Parting Thoughts: ServiceNow has always taken its vision of being the central hub for work and workflows seriously. It shouldn’t be a shock that accelerating their Agentic AI roadmap is their starting point for 2025. While the lowest hanging fruit will be those customers looking to create feedback, intelligence and optimization loops for Agents, the fast opportunity for ServiceNow could actually be back at their roots of service. For far too long we have taken a test-deploy-review-reset approach to bot deployment and optimization. But agentic AI and this age of generative AI as a foundation for multi-modal multi-channel engagements with customers, waiting for a report is already too late to resolve negative outcomes caused by hallucination or broken process. In flight optimization and the replication of a live-agent’s capacity to problem solve in the moment is the new tech requirement. And in the end, it is yet another way AI organizations can reveal and integrate another critical data source by turning chatter into data.

Marketing Transformation Next-Generation Customer Experience Tech Optimization Chief Customer Officer Chief Executive Officer Chief Information Officer Chief Marketing Officer Chief Digital Officer Chief Data Officer

ServiceNow acquires Cuein, aims to create AI agent feedback loop

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 said it will acquire Cuein, a startup that analyzes AI and human chat interactions. The company said the deal will accelerate its roadmap for ServiceNow AI Agents.

Terms of the deal weren't disclosed.

The thinking behind the acquisition is worth noting. Cuein provides a platform that understands and provides insights on customer interactions across systems.

What ServiceNow is hoping to do with Cuein is create a continual feedback loop that will make its AI agents more effective over time. Cuein measures conversations between humans and AI agents and gives enterprises the ability to address customer issues. Cuein also features inferred customer satisfaction scores for each exchange.

Constellation Research analyst Liz Miller said in a blog post:

"Cuein is about more about continuous improvement than it is about a tool for a specific function. In an age when agentic AI is being infused in almost every process and every interface in the enterprise, mining for patterns, flows, breaks and failures should be one of those ambient processes focused on improvement and optimization rather than reporting and post mortems."

Dorit Zilbershot, group vice president of AI Experiences and Innovation at ServiceNow, said in a statement that Cuein's ability to process data on the fly and provide real-time insights will give customers the ability to "unlock the full potential of agentic AI."

ServiceNow's plan is to integrate Cuein's capabilities into ServiceNow's Workflow Data Fabric.

The purchase of Cuein, founded in 2021, is expected to close in the first quarter.

More:

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Infosys sees 'good traction' with SAP S/4HANA migrations

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

Infosys CEO Salil Parekh said his company is seeing "good traction" with enterprises moving to SAP S/4HANA as well as the use of generative AI as enterprises look for efficiencies.

The comments from Parekh landed after Infosys reported its third quarter earnings, which fell short of expectations.

Infosys reported third quarter revenue of $4.94 billion with earnings of 19 cents a share. The company projected revenue growth of 4.5% to 5% for fiscal 2025.

Infosys research: AI Global Services: Infosys Topaz | Constellation ShortListâ„¢ AI-Driven Cognitive Applications | Constellation ShortListâ„¢ AI Services: Global | Constellation ShortListâ„¢ Innovation Services and Engineering

"We are seeing good traction on areas like SAP S/4HANA," said Parekh. "We are seeing good traction on cost takeout."

Parekh added that Infosys was seeing strong demand on SAP cloud migrations under the Rise with SAP program. "That work is more implementation of migration," said Parekh.

CFO Jayesh Sanghrajka added that "the S/4HANA migration deadline is driving budget allocation to make enterprise workloads compliant."

The SAP comments from Infosys follow a talk by UiPath at the Needham Growth Conference this week. UiPath CFO Ashim Gupta said the company's partnership with SAP has been a win-win due to the automation capabilities that help migrate to S4/HANA. SAP reports earnings Jan. 28.

Gupta said:

"The value proposition is two-fold. When you move to S/4HANA you want to customize it less. SAP calls it a clean core. To maintain a clean core, you can really do a lot of your customization through the automation that surrounds the ERP. You can automate upon delivery of the ERP or as a part of that implementation. That value proposition is felt by our customers. We've already seen some traction and some wins for it."

Infosys is also adding genAI agents to some of the financial processes that touch finance processes. Parekh said that invoicing is a key area.

According to Infosys, enterprises are showing interest in the company's small language models designed for specific tasks and process. Parekh added that Infosys is also using generative AI to deliver its own services.

Here's a look at some of the notable takeaways from Infosys' third quarter earnings:

  • "We are seeing an improvement in retail and consumer product industry in the U.S. with discretionary pressures easing," said Parekh. "Demand trends remain stable in other industries with clients continuing to prioritize cost takeout over discretionary initiatives."
  • "We have built four small language models for banking, for IT operations, for cyber and for enterprises broadly. These small language models have 2.5 billion parameters. These models are built using some of our proprietary datasets," said Parekh.
  • Infosys is developing more than 100 new genAI agents for clients. Parekh noted that Infosys has created a research agent for a product support team at a large technology company as well as three audit agents for a services firm.
  • Parekh said small language models are being used for software development, customer service and knowledge transfer in clients. Infosys is betting that it can deploy these models and then gain share by helping enterprises build their own models. "It's like having the model as a service," said Parekh.
  • AI budgets are broad-based and separate initiatives relative to the IT budget, said Parekh.
  • IT spending has picked up and enterprises are focused on cost optimization, AI, cloud adoption, cybersecurity and analytics.

More:

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SentinelOne enables its Singularity Platform, Purple AI to ingest data from rival security vendors

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

SentinelOne said its Singularity Platform and Purple AI security analyst can now ingest data from third-party security offerings including Zscaler Zero Trust Exchange platform, Palo Alto Networks Firewall, Okta, Proofpoint TAP, Fortinet FortGate, and Microsoft Office 365.

The move by SentinelOne, a smaller security vendor relative to the giants such as Zscaler, Palo Alto and CrowdStrike, has seen more interest from enterprises looking to resist the march toward platformization.

SentinelOne said the addition of third-party data to the Singularity Platform enables Purple AI to accelerate the automation of security investigations, prioritize threats and cut response times. Purple AI uses the Open Cybersecurity Schema Framework (OCSF) to query data that has been normalized on ingestion via natural language.

In addition, SentinelOne said it will support natural language queries and summaries in Spanish, French, German, Italian, Dutch, Arabic, Japanese, Korean, Thai, Malay and Indonesian.

Constellation Research analyst Chirag Mehta said the SentinelOne moves are likely to be well received by customers. SentinelOne is likely to have multiple joint customers with larger vendors. Mehta said:

"Cybersecurity is a team sport, and integrating telemetry from diverse third-party systems isn’t just valuable—it’s essential for enhancing security posture. As the drive toward platformization accelerates, it’s refreshing to see solutions that prioritize strengthening the SOC by collaborating with other security providers—even competitors—rather than confining customers within proprietary ecosystems. Additionally, as AI democratizes cybersecurity skills, multilingual support is a significant step forward, enabling organizations to leverage globally distributed talent to address today’s complex security challenges."

Key points about the SentinelOne innovations:

  • In a release, SentinelOne cited an out-of-the-box integration with Zscaler so customers can pull Zscaler Security Service Edge (SSE) into Singularity.
  • The company said in a blog post that Purple AI can handle natural language queries from security analysts.
  • Purple AI can also provide contextual follow-ups for more security insights.

 

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Cisco announces AI Defense, Protecting AI Investments and Applications | With R "Ray" Wang

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

📢 HOT OFF THE PRESS: Cisco announces AI Defense, a new product helping organizations protect their #AI investments and applications...

Hear Constellation founder R "Ray" Wang's take on why this product is important, particularly as AI becomes widely adopted and cyberattacks can happen at machine scale. Key benefits of Cisco AI Defense include:

📌 Visibility and control over third-party AI #apps to ensure they are secure and following policies
📌 Enabling developers to build and run AI apps without security issues
📌 Combining human and machine capabilities to fight AI-powered cyber attacks at scale

💡 To learn more about the AI Defense launch, hear from Cisco Chief Product Officer Jeetu Patel: https://fnf.dev/4gREMQ4

➡️ Register for a FREE virtual AI Summit on Jan. 22 @ 9 am PST to hear from global business leaders discussing challenges and opportunities of AI: https://lnkd.in/gcVbT2id

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Taking stock of quantum computing’s kerfuffle and what's next

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

For an industry that's allegedly 15- to 30-years from being useful there’s a lot of news being generated from quantum computing.

As previously noted, CxOs need to think through quantum computing and potential use cases even though there is a lot of noise surrounding the sector. The timeline to date goes like this:

  • Quantum computing pure play stocks took off at the end of 2024 due to Google's Willow quantum processor, which is a long way from production. Stocks surged past any reasonable valuation, but the run was great while it lasted.
  • Nvidia CEO Jensen Huang then said quantum computing is 15- to 30-years from being useful to corporations.
  • The merry band of quantum computing stocks were halved in some cases as investors realized that they may be a bit ahead of themselves.
  • Quantum computing vendors launched a flurry of news announcements about backlog, bookings and contracts. Quantum stocks rebounded.

You'd be forgiven for having a bit of whiplash over this quantum computing kerfuffle. However, we'd be remiss if we didn't highlight some of this week's quantum computing news, which is pretty significant.

Practical quantum computing advances ramp up going into 2025 | Quantum computing all in on hybrid HPC with classical computing

What now?

Going forward, you can expect a lot of volatility across the quantum computing sector. One thing I've been watching closely is the type of quantum computing technology used by vendors.

Given the various flavors of quantum computing it's not difficult to foresee a VHS vs. Betamax scenario emerging in the years ahead. You’d be advised to spread your use case bets.

Research:

Here's a look at the types of quantum computing and the vendors in that category.

  • Superconducting qubits are seen as general quantum computing options and vendors in this category include IBM, Google and Rigetti Computing.
  • Trapped Ion quantum computing has high fidelity and long coherence times. IonQ is the big player in this category along with Quantinuum, which was created by the merger of Honeywell's quantum unit and Cambridge Quantum.
  • Neutral atom quantum computing has the potential to scale better and QuEra is a player here.
  • Quantum annealing is designed for optimization over general purpose computing and D-Wave has championed this approach.
  • Topological quantum computing has the potential to be more fault tolerant and is an avenue being pursued by Microsoft. Topological quantum computing uses a concept similar to semiconductors using "anyons," which can arrange qubits into patterns.

Today, quantum computing chatter talks about the sector as if all the vendors are all using the same technique. Ultimately, CxOs will have to ponder use cases and how they align to the various flavors of quantum computing.

As quantum computing matures, the focus will likely go to the software layer and ways to abstract quantum computing instances. Given that nearly all quantum computing resources will be delivered through the cloud, the various technologies may not matter enough as long as your cloud provider offers a broad range of instances.

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Microsoft launches Copilot Chat, pay-as-you go AI agents

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

Microsoft launched Microsoft 365 Copilot Chat which brings its free chat experience for Microsoft 365 commercial customers to a broader base. The catch is that there are pay-as-you-go agent capabilities.

The news comes as Google Workspace dumped Gemini add-ons in favor of an increase in pricing. Google's model, which follows the playbook of Zoom and Adobe, is cleaner.

Microsoft's move is designed to bring copilots and agents to a broader base of employees. Copilot Chat can enable an entire workforce to use AI chat powered by OpenAI's GPT-4o, agents that are easily accessible and IT controls.

That last item is going to be critical since Microsoft has a consumption plan for Copilot Chat that will impact how enterprises approach agent democratization (and AI agent sprawl).

In a blog post, Microsoft outlined a few pay-as-you go agent scenarios. Agents created in Microsoft Copilot Studio will be available from Copilot Chat. Usage of agents is measured by messages and total cost is based on the sum of messages used by an enterprise. You can pay a penny per message or use pre-paid message packs via Azure at $200 for 25,000 messages a month.

Microsoft charges for agent responses and whether they are predefined, generated, grounded with information from Microsoft Graph and autonomous. Here's a breakdown:

Enterprises are going to have to experiment with consumption costs and models and what happens if agents are allowed to be created by an entire workforce. Microsoft outlined the following scenario:

  • A hypothetical agent might answer questions from customers on a website. Yesterday, it consumed 500 classic answers and 2,000 generative answers. Therefore, it would cost 4,500 messages, equivalent to $45 for that day.
  • A hypothetical agent in Copilot Chat uses data stored in Microsoft Graph to answer employee questions about HR policies. Yesterday, the agent consumed 200 generative answers and 200 tenant Graph grounding for messages. Therefore, it would cost 6,400 messages or $64 for that day.
  • A hypothetical autonomous agent responds to and routes inbound sales orders from customers. Yesterday, it consumed 100 generative answers, 100 tenant Graph grounding for messages, and 800 autonomous actions. Therefore, it would cost 23,200 messages or $232 for that day.

It's unclear how this model will play out for customers. One thing is clear: Your software vendors will be trying out a variety of agentic AI models throughout the year.

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