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.  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…...

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Constellation Research kicked off its Ambient Experience 2024 in Austin and the key theme was the intersection of data, artificial intelligence, digital transformation and employee and customer experiences.

Here's the recap of everything we learned.

Ambient Experience Summit | AX100 2024 | All AX Leaders

AI and data foundations

Generative AI is an immature technology that has put CIOs on the hot seat. Enterprises have to lead with privacy and trust before broad rollouts. "AI should not be used everywhere and some use cases don't apply. You can build it and they won't necessarily come," said Ghalib Kassam, CIO, Los Angeles Times.

AI will be critical to drive personalized and contextual experiences, said Robert Kleinschmidt, Senior Vice President, Marketing & Mil/Aero SBU AirBorn. AirBorn makes connectors and parts for harsh environments. The company is looking to build experiences focused on personas, context and personalization.

To drive these AI experiences, customers will have to gather data attributes across systems and types. Data will also be needed to focus on teams behind projects instead of individual leads. "In B2B, there are five, 10 or more people involved in a project," said Kleinschmidt. "The lead on a project is not a person. There are different journeys for customers, and you need to see the connections between individuals."

The biggest challenge for AI is convincing CEOs that data is the foundation, and you need to spend time and resources on the grunt work, said Kleinschmidt.

Generative AI could be "scary for enterprises and vendors," said Rob Tarkoff, Executive Vice President & GM, CX Applications at Oracle. Why? "As an industry this is the first time where we've had applications that we don't entirely know what they will do," said Tarkoff. "Incorporating new models creates a whole new frontier of prompt engineering. You test against synthetic data, and you run as many models, and you constrain prompt engineering as much as you can. In an enterprise context, you don't have as much margin for error."

Leadership

Anthony Noble, SVP, Chief Strategy Officer at American Tower Corp., said leadership requires building an understanding on how your colleagues contribute to the business and their knowledge bases. "After that you put together teams with different knowledge bases to solve problems." said Noble. "There's a power in learning together once you're past the scary part and understand the opportunities."

Don't get caught up on technologies because the lifespan of digits is much shorter than inspiring people, said Raju Vegesna, Chief Evangelist at Zoho.

Leaders are more influencers than commanders, said Constellation Research analyst Dion Hinchcliffe. "The biggest trend is that leadership has moved away from command and control," said Hinchcliffe. "Leaders are not order givers but influencers. You need employees to solve local problems at scale with innovation and creativity."

B2B customer experiences

The user journey, experience and interface need more attention in B2B companies. In many B2B companies digital UX has been an afterthought. Kimberlee Sinclair, VP of Digital Customer Experience at H.B. Fuller, said her team enabled transformation by melding technology and digital marketing. "We needed dotted lines between the technology and marketing for it to come together," said Sinclair. "Luckily, our CIO is a businessperson and not a technology wonk."

"Customer experience no longer rests with the sales team," said Trane's Portia Mount, Vice President of Marketing at Trane Commercial Americas, Trane Technologies. "Experience is the integration of product, sales and marketing teams if you want transformation."

Continuous upskilling will be required in the manufacturing sector amid generative AI and productivity gains. "How do we help people get smarter and faster?" asked Mount.

High touch doesn't mean a good experience. Chad Meley, CMO of Kinetica, said experience used to hinge on giving your best customers attention. "There's a pivot toward more self-service and meeting customer preferences to how they want to buy," said Meley.

Employee and customer experiences combine

Does employee experience drive customer experience? April Obersteller, Director of Global Experience: Employee Experience + Customer Experience at Woom Bikes, works at a company that puts employee and customer experiences under one leader. "We believe strongly that the customer is at the center and that has shifted to the employee experience as well," said Obersteller.

Bob DelPonte, Senior Vice President of Customer Success and Global Delivery Services at UKG, said he worked with his HR leaders to correlate customer satisfaction and employee engagement. "My lowest engaged team actually has the worst customer satisfaction systems. And so, when people say happy employees, happy customers, I can correlate directly to productivity, engagement and overall satisfaction," he said.

Employee experience needs to reduce friction. John Bollen, CIO at Blackstone Portfolio Companies, said reducing friction for employees across systems is critical to improving customer experiences. "We never call an employee an employee. They were co-star. Co-stars were part of the experience, and they were part of the show. Everyone was part of the show," said Bollen. "We have all these systems, all these different touch points and getting that data into the cloud so that any employee can look up the customer and understand who they are. It's UX and CX in your hand."

Retention is also a key metric behind employee experience efforts. "We're being very intentional, for the first time ever about the employee experience," said Darla Caughey, Director of Employee Experience at Austin Independent School District. "It's not typical to see an employee experience department in a public school district and it is making a difference with retention." Enterprises will need to have AI strategies and use cases to retain and attract employees.

Employee experience is getting focused on key personas. Christy Punch, Senior Mgr., Product Manager Engineering Experience at Liberty Mutual Insurance, said she's focusing on the developer experience at her company. "I've spent the majority of my career focused on employee experience. And so rather than going broader with customer experience, I've actually started to narrow my focus. And now I am focused on the engineering experience, which is more traditionally known in the industry, the developer experience, and that's actually a very hot topic," she said.

 

Marketing Transformation Future of Work Next-Generation Customer Experience Data to Decisions Innovation & Product-led Growth Tech Optimization Digital Safety, Privacy & Cybersecurity ML Machine Learning LLMs Agentic AI Generative AI AI Analytics Automation business Marketing SaaS PaaS IaaS Digital Transformation Disruptive Technology Enterprise IT Enterprise Acceleration Enterprise Software Next Gen Apps IoT Blockchain CRM ERP finance Healthcare Customer Service Content Management Collaboration Chief People Officer Chief Information Officer Chief Marketing Officer Chief Digital Officer Chief Data Officer Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Analytics Officer Chief Information Security Officer Chief Product Officer

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.  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…...

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Zoom Video Communications reported a better-than-expected fourth quarter, raised its first quarter outlook and said it would buy back $1.5 billion in shares.

The company reported fourth-quarter revenue of $1.15 billion, up 2.6% from a year ago, with net income of $299 million, or 95 cents a share. Non-GAAP earnings for the fourth quarter were $1.42 a share. 

Wall Street was expecting Zoom to report fourth quarter non-GAAP earnings of $1.15 a share on revenue of $1.3 billion.

Zoom expands reach, generative AI use cases with pricing that aims for market share

Zoom said enterprise revenue in the fourth quarter grew nearly 5% as online revenue, typically individuals and small businesses, fell less than 1%.

In prepared remarks, Zoom CEO Eric Yuan said:

"Since its launch only five months ago, we expanded AI Companion to six Zoom products, all included at no additional cost to licensed users. But we are far from done. Our future roadmap for AI is 100% guided by driving customer value. We are hard at work developing new AI capabilities to help customers achieve their unique business objectives and we’ll have more to share in a month at Enterprise Connect."

Yuan added that Zoom's Contact Center suite is beginning to win against incumbents. 

For fiscal 2024, Zoom reported net income of $637.5 million, or $2.07 a share, on revenue of $4.53 billion, up 3.1% from a year ago.

As for the outlook, Zoom said it expects first quarter non-GAAP $1.18 a share to $1.20, compared to estimates of $1.15 a share. Zoom said first quarter sales will be $1.13 billion.

Zoom said it had about 220,400 enterprise customers, up 3.5% from a year ago. Fourth quarter average monthly churn was 3%, down 40 basis points from a year ago. 

Future of Work zoom Chief Information Officer

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.  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…...

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Workday's delivered fourth-quarter sales that were slightly below expectations, but handily topped its earnings estimates. Separately, Workday said it will buy HiredScore, which specializes in talent orchestration.

The company reported fourth-quarter earnings of $4.42 a share, which includes a $1.1 billion tax benefit. Non-GAAP earnings for the fourth quarter were $1.57 a share on revenue of $1.9 billion, up 17% from a year ago.

Wall Street was looking for fourth quarter earnings of $1.47 a share on revenue of $1.92 billion.

For fiscal 2024, Workday reported revenue of $7.3 billion, up 17% from a year ago. Earnings were $5.21 a share.

Workday's subscription revenue backlog was $20.9 billion in the fourth quarter, up 27% from a year ago. Carl Eschenbach, CEO of Workday, said the company saw "continued momentum with full platform customer wins and expansions within our base." Workday's Eschenbach becomes sole CEO, Bhusri executive chair

As for the outlook, Workday CFO Zane Rowe said the company is reiterating its fiscal 2025 subscription revenue guidance of $7.725 billion to $7.775 billion. Non-GAAP operating margins will be about 24.5% as the company balances investment in the business with profits.

• Workday Doubles Down on the ‘Hard Stuff’
• Workday Q3 shows strength, raises outlook
• Workday lays out growth plans through fiscal 2027: Here are the takeaways

Rowe said the fourth quarter was solid. On a conference call with analysts, Eschenbach said the company is looking for growth outside of North America.

He said:

"International represents over half of our addressable opportunity yet is 1/4 of our revenues. We're working to change that, and we're seeing early signs of progress. In EMEA, our leadership additions continue to drive improved and more consistent results."

Japan and Australia are also growing markets. 

Regarding HiredScore, Workday said it will combine HiredScore's Talent Orchestration platform with its Talent Management and Skills Cloud. Terms of the deal, which is expected to close in Workday's first fiscal quarter, weren't disclosed.

Eschenbach said the following about the HiredScore deal:

"When you think about the addition of HiredScore, that we just acquired, along with our recruiting platform, our Talent Optimization platform and our candidate engagement platform, it gives us the ability to deliver a full suite for talent acquisition around how we identify talent, how we engage with them, how we source or recruit them and then how we retain them for internal mobility. So I am really confident in our ability to deliver a strong ROI to the recruiting and talent organizations, with us having what I think now is one of the best full platform suites for talent acquisition going forward." 

 

Data to Decisions Future of Work New C-Suite Innovation & Product-led Growth Tech Optimization Sales Marketing Next-Generation Customer Experience Digital Safety, Privacy & Cybersecurity workday AI ML Machine Learning LLMs Agentic AI Generative AI Analytics Automation B2B B2C CX EX Employee Experience HR HCM business Marketing Metaverse developer SaaS PaaS IaaS Supply Chain Quantum Computing Growth Cloud Digital Transformation Disruptive Technology eCommerce Enterprise IT Enterprise Acceleration Enterprise Software Next Gen Apps IoT Blockchain CRM ERP Leadership finance Social Healthcare VR CCaaS UCaaS Customer Service Content Management Collaboration M&A Enterprise Service Customer Experience Chief People Officer Chief Information Officer Chief Executive Officer Chief Data Officer Chief Digital Officer Chief Marketing Officer Chief Customer Officer Chief Human Resources Officer Chief Technology Officer Chief Information Security Officer Chief AI Officer Chief Analytics Officer Chief Product Officer

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.  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…...

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Mistral AI said it released Mistral Large, a next-gen text generation model that's designed to be on par with OpenAI's ChatGPT, Anthropic's Claude 2 and Google's Gemini Pro. Mistral AI said Mistral Large will be available on Microsoft Azure.

The Mistral Large launch with Azure availability follows AWS' announcement that Mistral AI models would be coming to Amazon Bedrock to join models from AI21 Labs, Anthropic, Cohere, Meta, Stability AI and Amazon. Amazon Bedrock will carry Mistral 7B, Mistral AI's first foundation model, and Mistral 8x7B, which can summarize text, answer questions, and generate code.

Here's why generative AI disillusionment is brewing | Constellation ShortList™ Artificial Intelligence and Machine Learning Cloud Platforms | Get ready for a parade of domain specific LLMs | Trust In The Age of AI | How much generative AI model choice is too much?

For Mistral AI, Azure and AWS can give the company more distribution for its models, which seem to be advancing almost weekly. Enterprises have been evaluating multiple models including smaller ones that are use case specific. Meanwhile, regulators have been looking into generative AI investments and partnerships such as Microsoft's deal with OpenAI.

Mistral Large is fluent in English, French, Spanish, German and Italian and has a 32K token context window. Mistral AI said it will first bring Mistral Large to Azure, which is most closely associated with OpenAI's ChatGPT. Hyperscalers are racing to offer model choices to enterprises. Mistral Large is also available on Mistral infrastructure La Plateforme in Europe.

Although Mistral Large and the Azure deal will garner the headlines. Mistral AI also said it launched Mistral Small, which is optimized for performance, latency and costs.

Also see: How Generative AI Has Supercharged the Future of Work | Generative AI articles | Why you need a Chief AI Officer | Software development becomes generative AI's flagship use case | Enterprises seeing savings, productivity gains from generative AI | Work in a generative AI world will need critical, creative thinking

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

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.  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…...

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KKR said it will buy Broadcom VMware's End-User-Computing (EUC) division in a deal valued at $4 billion. With the move, Broadcom can focus on VMware's business and EUC will become an independent company.

EUC will include Workplace One, a remote access digital workspace, and Horizon, as well as an autonomous workspace emerging roadmap. In a blog post, Shankar Iyer, senior vice president and general manager at Broadcom VMware's EUC division, said KKR will be dedicated to EUC's customer base and keep existing management in place.

During its December earnings conference call, Broadcom said EUC and Carbon Black, which wasn't included in the deal with KKR, has about $2 billion in annual revenue. Broadcom CEO Hock Tan said the EUC and Carbon Black had strong assets. "We’ll find good homes for them because there are a lot of very interested parties who are more than happy to take those assets. And we’ll be very, very thoughtful about where we put those assets eventually, simply because the customers of many of these two assets, many of the customers are also the same customers to the VMware Cloud Foundation," said Tan.

At VMware Explore in August, EUC outlined a series of AI integrations with its Anywhere Workplace platform as well as virtual desktop, endpoint management and security advances. Boeing was also referenced as a VMWare Workspace One customer at scale.

In a statement, KKR Managing Director Bradley Brown said the private equity firm will continue to invest in Workspace One and Horizon as well expand its partner support and go-to-market efforts. The deal is expected to close in 2024.

KKR portfolio companies in technology include BMC, Barracuda aPeoplend Cloudera. EUC rival Citrix was acquired by Vista Equity Partners and Evergreen Coast Capital in 2022 and later merged with Tibco.

With the EUC sale, Broadcom can focus on VMware, which has rattled some customers with its pricing changes.

• VMware mansplains to customers about model changes, subscription pricing, account upheaval
• Dell Technologies to exit commercial agreement with VMware
• Will VMware customers balk as Broadcom transitions them to subscriptions?
• BT150 CXO zeitgeist: AI trust, AI pilots to projects, VMware angst, projects ahead

 

Future of Work vmware Chief Information Officer

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.  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…...

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This post first appeared in the Constellation Insight newsletter, which features bespoke content weekly and is brought to you by Hitachi Vantara.

Equifax in 2024 will decommission mainframes and data centers in North America as it largely completes a cloud transformation that dates back to 2018. Now Equifax CEO Mark Begor is looking for more product velocity, artificial intelligence capabilities and competitive advantage.

The Atlanta-based giant is best known as a credit reporting agency but has a portfolio of products via an insights engine powered by multiple data stores financial services, mortgage, commercial and residential real estate, auto, healthcare, government and employer services to name a few.

Begor, speaking on Equifax's fourth quarter earnings call noted that cloud-enabled AI using a combination of proprietary models and Google Cloud's Vertex AI will enable the new Equifax.

BT150 Interview: Equifax's Manish Limaye on data architecture, transformation

"We are convinced that our new EFX cloud single data fabric and AI capabilities are delivering new differentiated products faster with better performance and will provide a competitive advantage to Equifax for years to come," said Begor.

Equifax's journey highlights how cloud migration, digital transformation and data architecture are required to move AI efforts ahead. Equifax has also invested in transformation as its mortgage business has suffered due to rising interest rates. Fewer refinancing and home mortgages mean less Equifax data services.

Among the key milestones for Equifax in 2023:

• 70% of Equifax revenue is in the new Equifax Cloud.
• Equifax decommissioned 7 data centers and migrated 37,000 customers to Equifax Cloud.
• Saved more than the targeted $210 million goal.

And in 2024, Equifax plans on the following:

• Completing the North America move to the cloud and migrate all customers to Equifax Cloud.
• Decommissioning mainframes completely as well as remaining North American data centers.
• Progressing with transformation efforts in Europe and Latin America.
• Saving an incremental $90 million a year in 2024.
• And have about 90% of revenue in Equifax Cloud with the majority of new models and scores being built with Equifax AI.

Begor noted that the cloud enabled Equifax has launched more than 100 new products a year for the last four years. In addition, average revenue per new product is up nearly 50% since 2021.

For 2023, Equifax reported net income of $545.3 million on revenue of $5.26 billion, up from $5.12 billion in 2022. The company's divisions include Workforce Solutions, Online Information Solutions, Mortgage Solutions and Financial Marketing Services.

Equifax cloud's journey

In 2021, Equifax outlined Equifax Cloud, a cloud native architecture designed for highly regulated data workloads. The launch of Equifax Cloud took $1.5 billion in investment.

Equifax Cloud was primarily built on Google Cloud, but Equifax in its annual report does cite Amazon Web Services and other vendors used for outsourcing.

According to case studies from Google Cloud and AWS, Equifax uses Google for its cloud data architecture and AWS to host mission critical applications.

Equifax said it built Equifax Cloud because it needed to build something once and then deploy across its markets with customizations that required little engineering.

Manish Limaye SVP, USIS Chief Architect & Head of Data Engineering Equifax, said in an interview at Constellation Research's Connected Enterprise 2023 the Equifax decision to build on Google Cloud had a lot to do with machine learning and AI expertise.

Limaye, a BT150 member, said:

"Equifax is deep into statistical modeling. AI, you knew was going to be big. We were one of the leaders in the explainable AI space. When we partnered with Google, it was more than just what I'd call run of the mill cloud transformation. We wanted a deep partnership with Google beyond Google Cloud into data engineering. We partner with them. We learn from them. They learn from us because we have the most complex data. There's also the value and security of the data."

The company's cloud transformation also had a lot to do with security. Equifax has argued that a distributed cloud architecture reduces the attack surface.

In Sept. 2017, Equifax announced a data breach that exposed 147 million people. The company settled with various regulators for $425 million to help people affected by the breach.

Limay said Equifax vowed to be a security leader after its data breach.

"That security commitment really meant rethinking and reimagining how we look at securing our data given the sensitivity of it. We came up with a proper security control framework and paired it with our cloud native capability. There is an ability to destroy and rebuild data at any time. When you pair security frameworks and cloud together you walk away with a very comprehensive security framework. That control framework gets translated into a series of technical requirements. It's a very rigorous process."

Equifax CFO John Gamble said the company will gain operating leverage in the second half of 2024 due to the cloud migration. "In 2024, cost savings we will generate from decommissioning of North American infrastructure in the second half of '23 will exceed the redundant system and migration costs we are incurring, generating about 30 basis points of margin benefit," said Gamble.

For Begor, Equifax's cloud transformation is also evaluated based on new product releases. Equifax tracks a Vitality index, which is a percentage of revenue in any given year derived from new product releases over the previous three years and current year.

Equifax's multi-cloud approach reshuffles vendors

As Equifax's cloud transformation evolved so did its contracts and core vendors.

Starting in its 2019 annual report, Equifax began showing cloud payments to Google Cloud and AWS. Its 2018 annual report focused on payments to IBM, which was cited as a key vendor.

Equifax also noted that its cloud transformation was also a risk. The company said in its 2019 annual report filed with the Securities and Exchange Commission: "We are transitioning and migrating our data systems from traditional data centers to cloud-based platforms. This initiative will place significant strain on our management, personnel, operations, systems, technical performance and financial resources and internal financial control and reporting function. In addition, many of our existing personnel do not have experience with native cloud-based technologies and, as a result, we have and will continue to hire personnel with such experience. This effort will be time consuming and costly."

Here's the breakdown of Equifax's vendor roster from 2018 to 2023:

2018: Equifax said it had separate agreements with IBM, Tata Consultancy Services, Fidelity Information Services and others to "to outsource portions of our computer data processing operations, applications development, business continuity and recovery services, help desk service and desktop support functions, operation of our voice and data networks, maintenance and related functions and to provide certain other administrative and operational services." Equifax said it paid IBM $49 million in 2018, $40 million and 2017 and $45 million in 2016.

2019: Equifax added Google and Amazon Web Services as core vendors along with IBM and Tata Consultancy Services. Equifax's future minimum contractual obligation to its technology vendors at this point was $296 million. IBM was paid $52 million in 2019. Equifax noted that its payments to technology vendors could vary based on the volume of data processed and "significant new technologies."

The company said it paid Google $14 million in 2019, up from $7 million in 2018. Payments to AWS weren't disclosed.

2020: Equifax had agreements with Google, AWS, IBM, Tata Consultancy Services and others for portions the functions outlined in previous years. Equifax's future minimum contractual obligation to its technology vendors was about $318 million at the start of 2021.

Equifax outsourced mainframe and midrange operations, help desk service, desktop support and network operations to IBM in various regions. IBM was paid $50 million in 2020. By this time, Google started gaining wallet share. In 2020, Google was paid $29 million, more than double its 2019 payment.

2021: Equifax again cited Google, AWS, IBM and Tata Consultancy Services as core vendors with the aggregate minimum contractual obligation remaining of $902.4 million going into 2022.

Of that sum, the minimum contractual obligation to Google was $520 million. In 2021, Google was paid $62 million. IBM was paid $51 million.

2022: Equifax's vendor lineup changed in 2022. Including Google Cloud, AWS, UST Global, Kyndryl (formerly a part of IBM) and others, Equifax's future minimum contractual obligation at the start of 2023 was $948 million. Google and AWS accounted for the majority of that sum.

In its 2022 annual report, Equifax disclosed that its future minimum contractual obligation to Google Cloud was $440 million with no individual year's minimum to exceed about $120 million. In 2022, Equifax paid Google $152 million, up from $62 million in 2021.

For the first time in a regulatory report, Equifax outlined its obligations to AWS for hosting mission critical applications. Equifax's future minimum contractual obligation to AWS was $222 million with no minimum to exceed about $52 million. Equifax paid AWS $74 million in 2022 and added that it paid AWS $58 million in 2021 and $43 million in 2020.

2023: Equifax cited agreements with Google, AWS, UST Global and Kyndryl with an aggregate minimum contractual obligation of $1.4 billion as of Dec. 31, 2023. The minimum contractual obligation to Google for the remaining term was $1 billion with no individual year to exceed $228 million. Google was paid $171 million in 2023, up from $152 million in 2022. AWS' future minimum contractual obligation was $173 million for the remaining term with no individual year exceeding $52 million. AWS was paid $52 million in 2023, down from $74 million in 2022.

Focusing on Equifax AI

With Equifax's cloud transformation mostly complete, Begor said the company is focusing on Equifax (EFX) AI, which leverages the company's internal data, proprietary data sets and models from its Ignite platform as well as Google Cloud Vertex AI.

"Our proprietary data at scale and our single data fabric leveraging our new EFX Cloud gives us significant advantages in using AI to build more predictive multi-data models, scores and products," said Begor. "Our EFX AI is enabled by our explainable AI solutions that leverage our Ignite platform and our Google Vertex capabilities."

Begor added:

"Our investments in AI are generating results. To date, Equifax has received over 90 approved AI patents supporting areas such as our proprietary AI NeuroDecision Technology, or NDT, an explainable AI with over 130 AI patents pending. We've launched new products developing at EFX AI, including Equifax OneScore for consumers incorporating traditional credit, alternative credit, as well as cell phone utility and pay TV data, which has improved the performance of the solution to score 20% more consumers."

The game plan is to connect more data sets with Equifax AI to create new combinations of data, products and services.

Leveraging Google Cloud's Vertex AI was also an easy leap since Equifax built its data architecture on Google Cloud too. Equifax's data fabric has grown over time, but it's an internal data warehouse with additional capabilities.

Limaye said:

"You have a variety of layers--governance, observability streaming, virtualization, catalog and other things. We built our data platform on top of Google Cloud technology, and we standardized the pipelines at every step. When the data comes, it goes through the initial cleaning and transformation. It also gets entity resolution and linking. There is no differentiation between the operation and the warehouse. Because on the one hand you are getting all this data, you're cleaning it up, and you're making it available for the product. We built our own data hub where we collect data for every platform, and it brings the operational data for different types of uses. We call it purpose views. You could use it for online transactions. There's also typical data warehousing using Google technologies where you can do analytics and marketing on top of Google Cloud."

With cloud savings and new AI-driven products for growth, Equifax is projecting 2024 revenue of $5.72 billion, up 8.6% from 2023. The company expects that its margins will expand due to organic growth and cost savings from its cloud migration. "As we look beyond 2024, the cost benefits of completing our cloud migration as well as accelerating high variable profit revenue growth are expected to drive significant improvement in EBITDA margins," said CFO Gamble.

 

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Data to Decisions New C-Suite Innovation & Product-led Growth Tech Optimization Future of Work AI ML Machine Learning LLMs Agentic AI Generative AI Analytics Automation B2B B2C CX EX Employee Experience HR HCM business Marketing Metaverse developer SaaS PaaS IaaS Supply Chain Quantum Computing Growth Cloud Digital Transformation Disruptive Technology eCommerce Enterprise IT Enterprise Acceleration Enterprise Software Next Gen Apps IoT Blockchain CRM ERP Leadership finance Social Healthcare VR CCaaS UCaaS Customer Service Content Management Collaboration M&A Enterprise Service Chief Executive Officer Chief Information Officer Chief Data Officer Chief Digital Officer Chief Technology Officer Chief Information Security Officer

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.  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…...

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Constellation Research held its February call with Business Transformation 150 and SAP's RISE program, process automation and AI were top-of-mind topics.

These gatherings, held under Chatham House rules, are a venue to share information and emerging trends. Here's a look at the topics from our February meetup.

Previously: BT150 CXO zeitgeist: AI trust, AI pilots to projects, VMware angst, projects ahead

SAP's RISE program

• One CIO asked the group for opinions on SAP's RISE program and being forced from on-premises to the cloud. The goal was to have a strategy for SAP in place by the end of the year.
• CXOs weren't thrilled about SAP RISE and items like licensing credits for legacy environments. A CIO wondered what would prevent a customer from moving away from SAP--especially since the enterprise operates in a space that doesn't garner investment from the enterprise software giant.
• One option could be to build a homegrown ERP system to replace SAP. 
• SAP's RISE program is viewed as an exercise in financial engineering more than something that benefits customers. 
• Being on-premises is actually a good thing because the customer isn't beholden to SAP and already paid for the asset. Rimini Street was frequently mentioned as an option for maintenance and support to preserve the initial SAP investment and keep options open down the road.
• For enterprises that don't want to migrate to SAP's cloud, there's an option to build an abstraction layer on top of the transactional system that's eating up budget without value.

Our BT150 CXOs aren't alone. SAP's German speaking user group takes aim at cloud contracts, BTP and more | SAP user group DSAG rips S/4HANA innovation plans, maintenance increases | SAP retools for generative AI, cuts 8,000 jobs, sets 2024, 2025 ambition

Process mining and automation

• Some CXOs were exploring proof of concept projects for process mining and modeling tools. The concerns revolved around process mining turning into more work than it needed to be unless the underlying systems were emitting real signals.
• Process mining was seen as an option to automate repetitive jobs. Celonis and SAP Signavio were mentioned as options.
• Process design is critical to making automation projects work.
• Enterprise automation needs processes that are designed by the bottoms up with employees on the front line. Enterprises should look to redesign processes completely and creatively destroy them to find new ways to work.
• Change management is a required art form to make automation work. In many cases, the objective for employees and departments is to maintain a process that has been running for decades. Resistance to change torpedoes automation projects and CXOs need to evangelize and bring in multiple stakeholders.

Celonis launches Process Intelligence Graph, makes case process enables automation, AI applications | SAP buys LeanIX, aims to couple it with Signavio, system transformation

Management tips

• Use regulatory and security requirements to move projects along and get stakeholders on the same page.
• Sell teams on projects that will last beyond today and influence the future. 
• Enterprise change is more successful if it starts from the inside than outside.
• Plan projects assuming that the CEO has a tenure of 4 years and so does the team attached to that leader. Year one is likely to be about cost cutting. Year two is about innovation funded by the savings of year one. Years three and four are about delivering results that renew the CEO's contract. The goal is to implement technology that can span leadership teams.

Return on Transformation Investments (RTI)

AI risks

• CXOs on our panel all referenced Air Canada's rogue bot that gave a discount that was upheld in court. There are other examples of bots giving deals that no human would approve. CXOs noted that safeguards, process maturity and a kill switch are required to prevent bots from becoming headaches.
• Enterprises need to think through where a human goes into a process to establish trust.
• Enterprises also need to ponder legal liability with generative AI.
• AI applications are becoming a key theme as enterprises look to renew long-term deals with software vendors. Multi-year deals may smooth out costs and contract negotiations.

 

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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.  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…...

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Reddit has filed to go public in a closely watched initial public offering and one of its potential revenue streams is data licensing. The big question is whether enterprises want that data in a large language model. Perhaps the bigger question is whether enterprises will have a choice.

The social community has made a deal with Google to provide it model training data. Reddit also indicated that it'll provide training data more broadly. Reddit has sentiment, conversational data, and a lot of useful stuff to go along with the ridiculous. In some ways, Reddit data is likely to make LLMs a bit more serendipitous.

Reddit's data licensing plan highlights how training data from media-ish companies is valuable. The plan also highlights Hobson’s Choice facing these companies. Reddit gets revenue by providing training data, but also could get squashed by an LLM in the future.

According to Reddit's S-1 filing with the SEC:

"Redditors may choose to find information using LLMs, which in some cases may have been trained using Reddit data, instead of visiting Reddit directly. We believe that our ability to compete effectively for users depends upon many factors both within and beyond our control."

Not that Reddit has a choice. Data licensing is a high-margin business and Reddit lost $90.8 million in 2023 on revenue of $804.03 million. The company did pare losses from 2022 and may be headed in the right direction if data licensing works out. Advertising is a rough business.

Reddit specifically names ChatGPT (OpenAI CEO Sam Altman is a shareholder of Reddit by the way), Gemini (Google paid Reddit for data) and Anthropic as competition. Reddit's list of competitors for your attention is also extensive: Google, Meta, Wikipedia, X, Snap, Roblox, Discord and any other company that can give you an answer. Marketplaces are also cited as rivals.

In other words, every Reddit competitor will also likely have a data licensing business. It's clear that users have become the product and the data licensing model.

As these data licensing models proliferate, data lineage is going to become critical. Ultimately, I'd want to know what data the LLM was trained on and be able to back out some sources. This ability is especially critical for media sources. Media isn't objective and you need a few outlets (and preferably source documents) to even figure out what the actual truth is. Media has become like navigating a divorce. There's the first spouse's truth. There's the other spouse's truth. And then THE truth.

• Shutterstock will bring its training data to Databricks, Snowflake, Amazon, Google Cloud
• Get ready for the generative AI training data licensing boom

• BT150 CXO zeitgeist: AI trust, AI pilots to projects

For companies like Shutterstock, which is going to provide training data for models on data marketplaces, the business looks more straightforward. Other providers can supply data, but in the end the LLM buyer may not actually want that data set. How do you reverse learning? How do you back out a data set? Do I want my customer service LLM dishing out some snarky comment it learned on Reddit, X or Meta properties? Is Reddit's training data really just a small subset of the company's more than 500 million visitors and 73 million daily active users that actually comment?

We should be asking these questions now because the data licensing parade is just about to leave the station. In its IPO filing, Reddit said it has "one of the internet’s largest corpuses of authentic and constantly updated human-generated experience" and is in the early stages of data licensing. Reddit said its platform is good for real-time perspective on products, market sentiment and signals. It'll provide data API access and model training from Reddit's real-time content.

Ideally, I'd want to see a nutrition label on LLMs, and a list of data sources used for training. I'd also want to check off sources too. It's unlikely we'll get those options, so enterprises are likely to find small language models aimed at specific use cases and industries more valuable. 

• Here's why generative AI disillusionment is brewing | Constellation ShortList™ Artificial Intelligence and Machine Learning Cloud Platforms | Get ready for a parade of domain specific LLMs | Trust In The Age of AI | How much generative AI model choice is too much?

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

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.  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…...

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Shutterstock is best known as a stock image provider and owner of Giphy, but the money and margins may come from training data for model training.

During the company’s fourth quarter earnings call, Shutterstock CEO Paul Hennessy said the company is looking beyond wholesale data deals with the likes of Meta and OpenAI to licensing data across marketplaces. Shutterstock sees the data business as something that can grow at a compound annual growth rate of 22% through 2030.

• GenAI trickledown economics: Where the enterprise stands today

Hennessy said:

"As we look ahead, AI and machine learning model training will continue to be a growth opportunity, especially as we look to diversify our revenue base by targeting new buyers beyond the hyperscalers. In fact, we just won our first seven figure contract involving a venture backed startup in the generative AI ecosystem, and we feel there are much more such opportunities ahead. We'll also be expanding our delivery model by leveraging our cloud marketplace partners. This will allow us to go from being a wholesale provider of data to the likes of Meta and OpenAI to a retail provider of data to the hundreds of companies we believe are going to custom train their own models.

To that end, we are in the process of rolling out Shutterstock's training data onto data marketplaces of DataBricks, Snowflake, Amazon and Google Cloud."

Shutterstock's data business had revenue of $104 million in 2023. Today, Shutterstock has 10 anchor customers for training data, but thinks it can get to 150 over time.

"The data marketplaces of Snowflake, Databricks, AWS and Google are comparatively small but fast-growing businesses for these companies as their customers learn how to enrich and monetize their own data and models," said Doug Henschen, VP and Principal Analyst at Constellation Research. "Interest in GenAI will further accelerate the growth of these data marketplaces as companies start to build their own small and midsize models, including ones harnessing image data."

Giphy has a role in this generative AI play for Shutterstock because the content platform is connected with APIs. That know-how has given Shutterstock "API relationships" with major technology players. Shutterstock will invest in 2024 to build out its training data business.

Hennessey said the plan is to bring Shutterstock data to where the customers are. "Our customers don't naturally think of Shutterstock as a place to go for computer vision training data and training their generative AI models, but they do typically go to a DataBricks or a Snowflake or an AWS or GCS in order to acquire training data. This is also the natural compute environment for these customers," said Hennessey, who added that those partners will boost distribution without hurting margins.

"The way these distribution channels make money is not by taking a cut of the data sales, it's through the compute. And so they're looking forward to having our data on their ecosystems, so they can drive additional compute in the cloud," he said.

It remains to be seen how Shutterstock's training data business develops. Contracts can last years or be shorter depending on volume-based pricing.

Shutterstock reported 2023 revenue of $874.6 million, up 6% from a year ago, with net income of $110.3 million.

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