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Meet the 150 Artificial Intelligence Executives Driving an AI Powered Future

We are excited and honored to announce the nominees for the inaugural 2024-2025 Artificial Intelligence 150 (AI150). The executives named on this year’s AI150 embody the characteristics and knowledge needed to challenge the status quo and push the envelope when it comes to disruptive forces and AI transformation.

With the boom of Generative AI, automation, and machine learning playing a pivotal role in accelerating digital transformation across all industries, these leaders embody the characteristics and knowledge needed to expand the AI agenda further to drive organizational and industry wide change. These leaders are pioneering what it means to be the first Chief AI Officer, thanks to their ability to balance stakeholder and shareholder interests with a clear focus on driving innovation and growth.

Over the past six months, AI150 nominations have been submitted by peers, industry influencers, technology vendors and analysts. It was a vigorous process to determine the final listing, and we are excited to recognize the executives today and at our first AI Forum on September 23, 2024, at the Harvard Club in New York City. 

Congrats again to the listed leaders:

  • Yaser Al-Onaizan, CEO at National Center of AI - KSA
  • Nabil Alnuaim, SVP, Technology and Digital at Aramco
  • Christopher Alvares, Chief AI Officer at USDA
  • Mike  Amend, Chief Digital Officer at Ford
  • Daniela Amodei, President at Anthropic
  • Sanjeevan Bala, Group Chief Data & AI Officer at ITV
  • John Beieler, Chief AI Officer at Office of the Director of National Intelligence
  • Yoshuo Bengio, Professor at University of Montreal
  • Jeff Beringer, Chief AI Officer at Golin
  • Garett Bernsten , Chief Data and AI officer at US State Department
  • Krishna Bhagavathula, EVP, Chief Technology Officer at the NBA
  • Parminder Bhatia, Chief AI Officer at GE Healthcare
  • Luther Birdzel, Chief AI Officer at Krista
  • Jason Birnbaum, Chief Innovation Officer at United Airlines
  • Michelle Bonat, Chief AI Officer at AI Squared
  • Jeff Boudreau, Chief AI Officer at Dell
  • Alix Boulnois, Chief Digital Officer at Accor
  • Rick Caccia, CEO at WitnessAI
  • Tina Chakrabarty, Global VP Sanofi Data AI Governance & Data Management at Sanofi
  • Krishna Cheriath, Chief Data Analytics Officer, head of AI at Zoetis Inc.
  • Robert Chilvers, Chief AI Officer at Newcross Healthcare
  • Bets Ciocca, Head of Apps and AI at the UK Ministry Defense
  • Mark Daley, Chief AI Officer at Western University
  • Anusha Dandapani, Chief AI Data Services at UNICC
  • Jason DaWayne Smith, Chief Growth Officer at Publicis Health Media
  • Bhavesh Dayalji, Chief AI Officer at S&P Global
  • Julie De Moyer, Chief Data and AI Officer at LVMH
  • Michael de Toldi, Chief Analytics Officer at BNP Paribas
  • Clément Delangue, Co-founder & CEO at Hugging Face
  • Li Deng, Chief AI Officer at Vatic Investments
  • Joe Depa, Senior Vice President - Chief Data and AI Officer at Emory University
  • Chandra Donelson, Chief Data and Artificial Intelligence Officer at US Department of Air Force and Space Force
  • Paul Dongha, Group Head of Data and AI Ethics at Lloyds Banking Group
  • Nicole Eagan, Chief Strategy & AI Officer at Darktrace
  • Shawn Edwards, CTO at Bloomberg
  • Ronke Ekwensi, Chief Data Officer at T-mobile
  • Rana el Kaliouby, Co-Founder and General Partner at Blue Tulip Ventures
  • Noémie Ellezam, Head of Artificial Intelligence at Societe Generale
  • Rebecca Finlay, CEO of Partnership on AI
  • Helena Fu, Director, Critical and Emerging Technologies at Office of Critical and Emerging Technologies
  • Bernard Gavgani, Global Chief Information Officer at BNP Paribas
  • Amandeep Gill, Tech Envoy of Secretary General at United Nations
  • Frédéric Gimenez, Chief Digital Officer at TotalEnergies
  • Kfir Godrich, Chief Innovation Officer at Blackrock
  • Tabitha Goldstaub, Chair of UK Gover AI Council at UK Government AI Council
  • Aidan Gomez, CEO at Cohere
  • Ian Goodfellow, Research Scientist at DeepMind
  • Matt Gormley, Professor at Carnegie Mellon University
  • Matthew Graviss, Chief Data and AI Officer at US State Department, USG
  • Lan Guan, Chief AI Officer at Accenture
  • Anjali Gupta Reddi, Chief Data Officer at Dow Jones
  • Demis Hassabis, CEO and Co-Founder at Deep Mind Google
  • Ruimin He, Chief AI Officer
  • Hanna Helin, Global Head of Technology Innovation at London Stock Exchange
  • Philipp Herzig, Chief AI Officer at SAP
  • Ryan Higgins, Chief Information Officer (CIO) (Acting) and Chief AI Officer at US Department of Commerce
  • Geoffrey Hinton, Professor at University of Toronto
  • Lambert Hogenhout, Chief Data and AI at United Nations
  • Jeremy Howard, Founder and R&D at Answer.AI
  • Emmy Huang, Co-Chair, AI at Adobe
  • Daniel Hulme, Chief AI Officer at WPP
  • Eric Hysen, Chief AI Officer at US Department of Homeland Security
  • Lila Ibrahim, COO, at Deepmind Google
  • Elena Ikonomovska, Chief AI Officer at Mnemonic
  • Radha Iyengar Plumb, Chief AI Officer at United States Department of Defense
  • Anand Iyer, Chief AI Officer at Welldoc
  • Alex Jaimes, Chief AI Officer at DataMinr
  • Steve Jarrett, Chief AI Officer at Orange Group
  • Gila Kamhi, Chief AI Officer at Intel
  • Andrej Karpathy, Senior Director of AI at Tesla
  • Pankaj Kedia, Chief AI Officer at Biossmann
  • Matthias Keller, Chief Science Officer at Kayak
  • Hiroaki Kitano, Chief Technology Officer at Sony AI
  • Bulent Kiziltan, Global Head of AI & Computational Sciences at Novartis
  • Raghu Kulkarni, Chief AI Officer at Equifax
  • Samir Kumar, VP of AI at Fortive
  • Yann Lecun, Chief AI Scientist at Facebook/Meta
  • Sebastien Lehnherr, CIO/CTO, Strategic C-level Tech and Operations Executive, Independent Board Director and Advisor at SLB
  • Matt Lewis, Chief AI Officer at Inizio Medical
  • Fei-Fei Li, Sequoia Professor of Computer Science at Stanford University
  • Kacper Łodzikowski, Vice President, AI Capabilities at Pearson
  • Vilmos Lorincz, Managing Director, Data and Digital Products, Corporate and Institutional Bank at Lloyds Banking Group
  • Ken Lovell, Senior Vice President of Golf Technology at PGA Tour
  • Yuan Luo, Chief AI Officer at Walmart and Northwestern University
  • Christopher Manning, Director, Stanford Artificial Intelligence Laboratory at Stanford University
  • Vipin Mayar, VP, Head of AI at Fidelity
  • Jeff McMillan, Managing Director at Morgan Stanley
  • Walid Mehanna, Chief Data and AI Officer at Merck
  • Prakhar Mehrotra, Managing Director of Applied AI at Blackstone
  • Joshua Meier, Chief AI Officer at ABSCI
  • Nitzan Mekel-Bobrov, Chief AI Officer at eBay
  • Rashmi Misra, Chief AI Officer at Analog Devices
  • Alvise Montini, Head of AI Center of Excellence at Swarovski
  • Juergen Mueller, Chief Technology Officer and Executive Board Member at SAP
  • Jason Nadeau, Chief AI Officer at Fidelity
  • Detlef Nauck, Head of AI & Data Science Research at BT
  • Phong Nguyen, Chief AI Officer at FPT Software
  • Itaru Nishizawa, Chief Technology Officer at Hitachi
  • Jim Olivier, VP Analytics, Data, and Insights at eBay
  • Robert Opp, Chief Digital Officer at UNDP
  • Colin Parris, VP, Chief Digital Officer at GE Digital
  • Bhavik Patel, Chief AI Officer at Mayo Clinic
  • Divya Pathak, Chief Data Officer at NYC Health + Hospitals
  • Andrea Phua, Senior Director at AI- Ministry of Communications and Information
  • Carolina Pinart, Group Head of R&D Information Technology at Nestle
  • Andy Quick, Chief AI Officer at Entergy
  • Golestan (Sally) Radwan , Chief Digital Officer at UN Environment Program
  • Marc Raibert, Executive Director, The AI Institute
  • Philippe Rambach, Chief AI Officer at Schneider Electric
  • Jair Ribeiro, Analytics and Insights Leader at Volvo
  • Rob Ringham, Chief AI Officer at Artisight
  • Sean Ringsted, Chief Digital Officer at Chubb
  • Jose Rodriguez, Chief AI Officer at Lockheed Martin
  • Ruslan Salakhutdinov, Professor at Carnegie Mellon University
  • David Salvagnini, Chief AI and Data Officer at NASA
  • Casey Santos, CIO/CTO, Strategic C-level Tech and Operations Executive, Independent Board Director and Advisor at Vanderbilt University
  • Ashutosh Saxena, Cofounder, Chief AI Officer at Caspar
  • Kalyani Sekar, Chief Data and AI Officer, Verizon
  • Aymen Shabou, CTO of DataLab Group and AI Factory Group at Groupe Crédit Agricole
  • SK Sharma, Chief AI Officer at Universal Music Group
  • Prag Sharma, Global Head of Artificial Intelligence at Citigroup
  • Vijay Sharma, Chief Technology Officer at US Department of Education
  • Akshay Sharma, Chief AI Officer at Lyric
  • Janet Sherlock, Chief Digital Technology Officer at Ralph Lauren
  • Oodaye Shukla, Chief AI, Analytics, and Data Officer at Havas
  • Vinay Vijay Singh, Chief AI Officer at US Department of Housing and Urban Development
  • Satnam Singh, Chief Data and technology Officer at CBRE
  • Greg Singleton, Chief AI Officer at US Department of Health and Human Services
  • Alex Smola, CEO and Co-founder at Boson AI
  • Richard Socher, CEO at You.com
  • Stela Solar, Director, National Artificial Intelligence Centre at National AI Centre
  • Deep Ratna Srivastav, SVP head of AI at Franklin Templeton
  • Diane Staheli, Assistant Director, AI Applications at White House Office of Science and Technology Policy
  • Mustafa Suleyman, CEO at Microsoft.AI
  • Minerva Tantoco, Chief AI Officer at NY Hall of Science
  • Jaime Teevan, Chief Scientist at Microsoft
  • Ayesha Temuri, Enterprise Data Office at Telenor
  • Sunayna Tuteja, Chief Innovation Officer at Federal Reserve
  • Vishwajeet Uddanwadiker, Chief AI Officer at Boeing
  • Greg Ulrich, Chief AI Officer at Mastercard
  • Raquel Urtasun, CEO and Founder at Waabi
  • Eileen Vidrine, Chief AI Data Officer at US Airforce
  • Maksims Volkovs, SVP, Chief AI Scientist at TD
  • Katia Walsh, Chief Digital Officer at Harvard Business School
  • Shawn Wang, Chief AI Officer at Elevance Health
  • Andrew Wells, Chief AI and Data Officer at NTT Data
  • Richard White, Chief Data Officer at New York Life Insurance Company
  • Zach Whitman, Chief Scientist and Chief AI Officer at GSA, US Gov
  • Byron Yount, Chief Data and AI Officer at Mercy
  • Alex Zhavoronkov, CEO at Insilico Medicine


This prestigious recognition and induction ceremony will be held at Constellation’s AI Forum in September 2024.

For more details about the listed executives, visit: https://www.constellationr.com/artificial-intelligence-150-2024-2025
 

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Tableau CEO Aytay on genAI, the future of analytics, precision decisions

Tableau President and CEO Ryan Aytay said the company's future as part of the Salesforce product portfolio is to leverage generative AI in the future to offer "precision decisions" and a semantic layer that can democratize analytics and enable data sharing.

Aytay's appearance on DisrupTV was a month after Tableau's user conference. The company announced extensibility and usability feature and free local file sharing in Tableau Desktop Public. Tableau also announced Einstein Copilot for Tableau in beta, Tableau Pulse, which connects KPIs and insights, and Tableau+, a package for customers that want to provide access across an enterprise.

Tableau also launched more than a dozen new features that were showcased at the conference.

Tableau and Salesforce Eye Next Wave of Analytics and BI | Analytics and Business Intelligence Trends in Cloud, Embedding, and Generative AI

Before becoming CEO at Tableau, Aytay was the company's Chief Revenue Officer (CRO) for more than a year. Prior to Tableau he was Salesforce's Chief Business Officer. Here are some of the key takeaways from Aytay's DisrupTV chat.

The transition to Tableau CEO. Aytay's position as Tableau's revenue chief gave him a lot of opportunities to "learn the business and learn our customers." Aytay said the CRO role requires you to listen to customers and partners and see what's working and not and how to improve the experience.

"One of the key things for any role you start is that you have to be aware of what's happening and not just assume you know the answer because often you only know your own perspective," said Aytay.

 

Working with Tableau's community. One of the more unique things about Tableau is that it has a strong community of more than 4 million members. That tally has doubled since Salesforce acquired Tableau in 2019. "The community is a really big part of the business and an opportunity for customers and partners to learn from each other," said Aytay. "The community helped to bring training materials to learn and transition into the world of self-service analytics. Now we're into this core personalization and consumerization which is all about AI. The community is helping people move in that direction. It's a support system and ecosystem. My job is to really listen to them."

Aytay said he met with 30 customers in June to talk shop and everyone has been experimenting and trying to figure out the role of the digital worker. "I think we're still in the mode of the human interacting with a kind of digital worker," he explained. "In the longer term, the digital worker will become better and there will be a partnership with the technology."

Constellation Research analyst Doug Henschen said in a recent research note:

"Given that some 70% percent of Tableau customers do not use other Salesforce products, Tableau execs struck all the right chords to reestablish the importance of the brand and the DataFam, and to reinforce Tableau’s differentiation as a best-of-bread analytics and BI market leader. At the same time, they also acknowledged that Salesforce, with its deep pockets, its huge ecosystem, and its bevy of existing tech assets, will be indispensable and inseparable in helping Tableau to evolve."

Community and product development. Aytay said Tableau's product development is heavily influenced by the community because it "is the most in tune with what's happening."

"What's happening and what product requirements do we need to be thinking about. The community is like this heartbeat, and we need to do a lot for them, and they do a lot for us. It's a partnership. The best products have a strong community.

One of the best parts of my job is that I get to talk to the community members. I can tell you that we get a lot of feedback and that we need to change things. We're already talking to them about what's coming to give us feedback. They give us a bunch of feedback, and we try to make adjustments to things we don't always get right. You just have to be authentic and walk into these situations and talk about listening. Once you receive information you have to act on it."

Generative AI and safety. Aytay said generative AI has gone a long way to consumerizing AI, but it's still uncertain how it applies to the enterprise. "What's great about generative AI is that it has a lot of momentum. In a business or enterprise, you need to make sure you have a big data strategy to make sure you're not sending your company information into the open Internet," he said. "That's the journey and we can go with our community to teach businesses, organizations and nonprofits to be careful. I think we're in a learning environment right now."

GenAI and Tableau. Aytay said:

"First of all, we have to deliver what customers need right now. We've delivered products to the market that are useful. We have Einstein Copilot for Tableau, and it has been rapidly adopted.

But as we look to the next wave, the future of Tableau is really about going beyond seeing and understanding your data and that standard intelligence experience."

Aytay said companies have multiple data silos and your data has to support multiple people and roles. What's needed is a semantic layer that will bring all the data together a unifying it. That's a key part of Tableau's new products.

Marketplaces and sharing will also be a big part of the product roadmap. Aytay said:

"If there's a great visualization, data, data prep, data calculation or semantic model I should be able to share it in my four walls of the business and externally. That sharing is a radical change that is being built natively with AI."

Precision decisions. Aytay said that enterprises should be able to ask questions of the business in the flow of work in real time. The vision of analytics has been about actually making decisions in business.

"It's not just about looking at dashboards," said Aytay. "How do I make the best decision possible leveraging all the data in my business?"

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Education tech in turmoil amid genAI: Why consolidation is next

The education technology market has been rattled by generative AI, cautious enterprise and institutional spending and a set of overlapping companies with similar annual revenue profiles.

What's next? A merger and acquisition wave that's just getting started. The jockeying for position is already underway, but private equity will roll these companies together or they’ll merge on their own.

  • In March, Accenture said it will acquire Udacity and absorb its employees to create Accenture LearnVantage. Accenture's plan is to use LearnVantage to reskill and upskill people in technology, data and AI.
  • In May, Bain Capital said it will acquire PowerSchool for $5.6 billion. Meanwhile, Coursera and Chegg have been crushed by investors and now may look like buyout targets.
  • Instructure Holdings, the company behind Canvas, is reportedly in play to go private again. Thoma Bravo, which already owns 83% of Instructure, acquired the company for about $2 billion in 2020 and then took it public a year later at $20 a share. Now Reuters reports that Thoma Bravo is gauging private equity interest in Instructure. Instructure's market cap today is north of $3 billion.

Here's a look at the education technology players and what they're planning for the reskilling boom that has yet to arrive.

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

Coursera: Reskilling in genAI era tricky

Coursera has three operating units--consumer, enterprise and degrees. Consumer revenue was up 18% in the first quarter compared to a year ago and enterprise and degrees revenue was up 10%. AI courses were driving demand in consumer and building in enterprise and degrees.

What's the problem? Coursera's first quarter results were mixed and the second quarter outlook disappointed.

Simply put, Coursera has been in the penalty box since April. Coursera CEO Jeff Maggioncalda said, "we remain in the early stages of understanding how generative AI will reshape the way we live, learn and work."

Nevertheless, Coursera's plans and platform look solid. The company did see softness in North American subscribers, but has plays in higher-ed as well as corporate reskilling. The company is also using genAI to bolster its content.

Coursera has more than $725 million in cash and short-term equivalents and a market cap of $1 billion.

Chegg in turmoil

Chegg showed strong growth during the Covid-19 pandemic and has since struggled with declining subscriptions and fears that generative AI will hamper future business.

The company has swapped CEOs and cut headcount by 23%, or about 441 employees. In April, Chegg said second quarter revenue will be between $159 million to $161 million, a range that was well below Wall Street estimates.

In a shareholder letter that went along with its restructuring, new CEO Nathan Schultz said the company is going all-in on generative AI to offer better learning experiences. Schultz added that Chegg will provide 360-degree individualized support for students that will couple proactive guidance and a combination of AI, content and human experts.

Schultz said the plan is to become more efficient, consolidate platforms and expand internationally. Chegg will also ink commercial agreements with educational institutions. Typically, Chegg has marketed directly to students. "We plan to roll out an expanding marketing and branding program, build more AI-driven functionality and tools, localize our services internationally and layer in new non-academic offerings that address the whole student," said Schultz.

For now, Chegg needs to return to subscriber growth and remains in the penalty box. Chegg could also look enticing to private equity due to its brand with students and reality that transformations are best done without the quarterly results grind.

 

Instructure's powerful position with Canvas

It's unclear where Instructure shares would be without the report that Thoma Bravo is shopping the company. It's quite possible that Instructure would fall along with the rest of the education technology space.

Nevertheless, Instructure's position with Canvas--the education operating system is valuable. In its first quarter, Instructure reported revenue of $155.5 million, up 20.7% from a year ago. The company reported a net loss of $21.1 million.

The company guided to second quarter revenue of $166.5 million to $167.5 million with non-GAAP operating income of $66 million to $67 million. For the fiscal year, Instructure is projecting revenue of $656.5 million to $666.5 million with non-GAAP net income of $123 million to $127 million.

Here's the rub: Instructure has total debt of $1.17 billion as of March 31.

CEO Steve Daly said Instructure will continue to innovate with the Canvas Learning Management System (LMS) and be a cog in education digital transformation projects. Daly added that the education market is uncertain, but demand interest remains strong.

Daly said:

"The consolidation and optimization of technology resources continues to be a high priority, and the LMS is the natural place for consolidations to happen. Customers are pulling us into more broad-based digital transformation discussions and see Instructure as a platform for consolidating their tech stack. This is a long-term trend, and we believe our expanding portfolio of products, especially our EdTech effectiveness solutions, as well as the extensive reach of our partner ecosystem position us as the partner of choice for consolidation."

Instructure could be a consolidator in the education technology market. In February, Instructure completed the purchase of Parchment, which operates an academic credential market platform.

PowerSchool going private

PowerSchool is being acquired for $5.6 billion, or $22.80 per share, by Bain Capital. PowerSchool, which makes software for the K-12 education market, supports more than 55 million students and 17,000 customers.

The company announced the general availability of PowerSchool PowerBuddy, a generative AI assistant for teachers and students that personalizes learning plans to improve student engagement.

PowerSchool went public at $18 a share in 2021 and was trading in the $16 range before the Bain purchase.

In the first quarter PowerSchool reported revenue of $185 million, up 16% from a year ago. The first quarter net loss was $22.8 million. Annual recurring revenue (ARR) was $720.3 million.

Udemy: Rides AI training wave

Udemy reported first quarter revenue of $196.8 million, up 12% from a year ago, with a net loss of $18.3 million. Non-GAAP net income was $5.3 million.

The company is focused on online skill development and has more than 16,000 enterprise customers.

Udemy looks more like Coursera in that it has consumer and enterprise businesses. The company projected second-quarter revenue of $192 million to $195 million and annual revenue of $795 million to $805 million.

Gregory Brown, CEO of Udemy, said on the company's first quarter earnings call said:

"Udemy is differentiated by the high quality, immersive and localized learning experiences we provide. Our comprehensive solution is purpose-built to provide three essential learning modalities, on-demand, immersive and cohort based. This combination allows us to offer an end-to-end solution where professional learners and organizations around the world can easily identify and quickly develop the skills, they need to deliver better business outcomes today and in the future." 

In addition, Udemy has been riding the AI training and IT certification wave. "In just over a year since Chat GPT launched, we’ve seen more than 4 million enrollments in the 2,000 plus AI courses in the Udemy catalog," said Brown. "This massive surge in interest from individuals and organizations demonstrates the rapidly growing need to upskill talent on generative AI. Based on what we’ve seen in the past year, we believe generative AI will have a significant lasting impact across nearly every industry, region and professional role."

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Cognizant Takes Flight: Acquisition of Belcan Signals Aerospace and Federal Ambitions

Cognizant has announced its acquisition of Belcan, a leader in Engineering, Research, and Development (ER&D) services. This $1.29 billion deal, involving both cash and stock, is expected to close in the third quarter of 2024. The acquisition will significantly bolster Cognizant’s ER&D capabilities and diversify its client base into high-growth A&D markets. 

How This Acquisition Benefits Cognizant

The acquisition presents several advantages for Cognizant:

  1. Market Expansion: Belcan grants Cognizant access to the high-growth ER&D services market, expected to reach $255 billion by 2026 and grow at a CAGR of over 10%. A&D, a particularly strong segment within ER&D, is expected to grow at an even faster pace of 12-13% CAGR.
  2. Synergy and Growth: Cognizant anticipates over $100 million in annual revenue synergies within three years through cross-selling its services to Belcan's established client base and vice versa. The combined entity will also be able to scale its global delivery capabilities to address the growing demand for outsourced engineering services in the commercial aerospace sector.
  3. Leadership in A&D: Belcan brings to the table a strong reputation and long-standing relationships with blue-chip clients in the A&D industry. This will allow Cognizant to establish itself as a leader in this lucrative sector. 27 of the top 30 Belcan’s clients are Global 2000 companies or the US Federal Government.
  4. Onshore Workforce Expansion: With 85% of Belcan’s 6,500 employees based in North America, Cognizant significantly strengthens its onshore capabilities, addressing the growing client demand for near-site technical expertise.

Impact on the ER&D services market

The acquisition sets a new benchmark in the ER&D services market. Cognizant’s enhanced capabilities and expanded client base will intensify competition, particularly in the aerospace and defense sectors. Other major players may need to reconsider their strategies and potentially seek similar acquisitions to maintain their market positions. Additionally, the deal underscores the importance of onshore capabilities, potentially influencing workforce strategies across the industry.

The IT and engineering services landscape is constantly evolving. This acquisition is likely to accelerate the convergence of these two domains. We can expect to see other major IT services providers following suit and inorganic growth through acquisitions becoming a prominent strategy.

Source: Belcan

How AI Can Revolutionize ER&D Services

AI is poised to revolutionize the ER&D services domain. Cognizant, leveraging Belcan’s expertise, has potential to harness AI to drive innovation and efficiency in several ways:

  1. Predictive Maintenance: AI can analyze vast amounts of data from aerospace and defense systems to predict failures and optimize maintenance schedules, reducing downtime and costs.
  2. Design and Simulation: AI-driven design tools can enhance the accuracy and speed of engineering simulations, leading to more efficient product development cycles.
  3. Enhanced Automation: AI can automate routine engineering tasks, allowing skilled engineers to focus on more complex and creative aspects of projects, thereby increasing productivity and innovation.

Recommendations for CxOs

  • Reassess Vendor Partnerships: With Cognizant's enhanced capabilities, CxOs should re-evaluate their ER&D service provider relationships. The combined entity may offer unique value propositions, especially for companies operating at the intersection of IT and engineering.
  • Explore Integrated Service Models: Consider how the convergence of IT and engineering services could benefit your organization. Integrated service models could lead to faster innovation and more cohesive product development cycles.
  • Prepare for AI-Driven Engineering: Start building internal capabilities to leverage AI in your engineering processes. Partnering with providers like the new Cognizant-Belcan entity could accelerate this transition.
  • Monitor Industry Consolidation: Keep a close eye on further consolidation in the ER&D services market. This acquisition could trigger a series of similar moves, potentially affecting service availability and pricing.
  • Invest in Talent Retention: With the growing importance of domain expertise and long-term client relationships in ER&D services, redouble efforts to retain key engineering talent within your organization.
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Data centers in space: Feasible, sustainable and could drive returns

Data centers in space are economically feasible and could reduce carbon emissions as workloads for generative AI surge, according to Thales Alenia Space, the coordinator of a European Commission study.

In a statement, Thales Alenia Space, a joint venture between Thales and Leonardo, said that space-launched data centers could drive returns of several billion euros between now and 2050 while moving the EU to net-zero carbon in the same time frame.

The study included expertise from environmental experts (Carbone 4, VITO), cloud computing (Orange Business, CloudFerro and HPE), launchers (ArianeGroup) and orbital systems (Germany's space agency, Airbus and Thales Alenia Space).

Space-based data centers are a topic that's folded under the European Commission's Horizon Europe program. This space cloud for Europe concept falls under a program called ASCEND (Advanced Space Cloud for European Net zero emission and Data sovereignty).

Key points in the feasibility study include:

  • Developing and operating data centers in space would significantly reduce CO2 emissions.
  • Data centers in space would not require water cooling and could run on solar power.
  • The big issue is that a launcher would need to be developed that is 10 times less emissive over its life cycle.
  • Returns on investment would justify building a high-capacity, environmentally friendly reusable launcher.
  • Modular space infrastructure would be assembled in orbit using robotics from the EC's EROSS IOD (European Robotic Orbital Support Services In Orbit Demonstrator) led by Thales Alenia Space, scheduled to fly its first mission in 2026.
  • The ASCEND project would also support Europe's digital sovereignty.

The partners in ASCEND now plan to flesh out the feasibility study and optimize the results with the aim of building out a roadmap for deployment in 2030.

Will we see data centers in space soon? It's unclear. The feasibility study noted that development plans would require European supply chain support, space access, orbital servicers, in-orbit assembly and manufacturing. However, it's possible that private sector entities could pursue similar plans.

Bottom line: Space data centers could cover a bevy of bases--data sovereignty, sustainability and capacity--issues and are worth pursuing.

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Ian Cole’s CX Mission at Give Kids The World Village: 'Do Amazing Things'

For Ian Cole, chief innovation officer of Give Kids The World Village (GKWV), returns on technology investments are measured in smiles.

GKWV is an 89-acre nonprofit “storybook” resort in Kissimmee, Florida, that gives children with critical illnesses and their families from around the world week-long cost-free vacations.

The goal of GKWV is straightforward and laudable: give families that may have never had a vacation due to challenges an experience that will last a lifetime. Since 1986 GKWV has served more than 200,000 families from all 50 U.S. states and 77 countries, enabling them to laugh, play, and create unforgettable memories away from hospital stays and medical treatments.

“Customer experience is important no matter what you’re doing, but I think it’s especially important if you’re in the nonprofit world and you’re trying to do good for groups of people in despair,” says Cole. “You’ve got to make sure that every one of the people involved has a great experience, whether it’s a volunteer or a donor or the end beneficiary of what you’re doing.”

Cole, who leads the IT team that oversees networks, applications, security, mobile and desktop devices, and interactive experiences, worked with Avaya Customer Experiences Services (ACES) to give technologies to the onsite guest support team for creating guest experiences. His efforts at GKWV made him a CX for Good winner in Avaya’s CX Force Awards.

For Cole, technology projects aim to address current challenges and set up the future. He recently used Avaya to move from analog lines to Session Initiation Protocol (SIP) to boost reliability while cutting costs, implement a system for 911 emergency responders, and upgrade cloud and artificial intelligence (AI) features. GKWV uses Avaya unified-communications-as-a-service (UCaaS) and Avaya contact center solutions.

Related: How Virginie Nowak blended employee and customer experiences at Access Bank

GKWV has unique communications needs, because it is located in Florida’s Lightning Alley and needs to ensure uptime. The communications systems also need to ensure that responders have the necessary information about their clients, who may have unique health issues.

Here’s a look at some of the technology projects planned with ACES to enable the guest services team to personalize visits:

  • Machine translation to give guests an experience in their native language. GKWV’s services support teams speak primarily English and Spanish.
  • A digital scavenger-hunt bot for guests on the day of arrival. The bot enables parents to explore the village while children engage in an activity. Clues are readable on any smartphone and can be played back with text-to-speech.
  • A concierge bot for navigation and guest information in multiple languages.
  • A bot that enables volunteers to rapidly get answers and sign up for available slots.

These projects have to run on a tight budget, so GKWV does the best it can with the dollars entrusted to it by donors. “As a nonprofit organization, it’s very important for us to make sure that we pick the tools, technologies, and processes that we can support, both financially and technologically,” says Cole. “It would be very easy to chase the latest and greatest thing, but we’ve got to make sure that we’ve got the partnerships, relationships, and internal team to support those things. If we get that right, we can do amazing things.”

As for returns, Cole’s contributions to GKWV are measured in smiles. Each wish child can personalize a gold star for Stellar the Star Fairy to place on the ceiling of the Castle of Miracles and the Star Tower. The facilities—including pools and rides—are accessible to all children. And GTKW is planning to launch Mayor Clayton’s WonderLab STEAM Education Center this year.

Other 2024 CX Force Winners include:

  • CX for Education. Tara Pasalic, systems integration specialist, McMaster University. Pasalic is an early adopter of cloud contact center as a service and a longtime Avaya customer. McMaster University focused on improving experiences for international students leveraging Short Message Service (SMS) messaging and call center resources.
  • CX for Employees. Jayne Hogle, director of Unified Communications, American Heart Association. According to Hogle, customer experience at the American Heart Association is really about being heard. The technology plan has focused on everything from automated responses to call-to-ticket workflows and self-service tools made possible with a migration to the cloud. 
  • CX for Healthcare. Rafael Sousa, chief technology officer, Hospital Nipo-Brasileiro (HNIPO). Sousa led an effort to link customer experience, hospital operations, and patient outcomes. Leveraging Avaya, Sousa has been able to provide faster and more personalized assistance to patients and route them to appropriate departments.
  • CX for Growth. Hugh Carr, director of Customer Services, Standard Focus. Carr has been able to leverage Avaya customer experience technologies to improve experiences and boost revenue growth. By focusing on customer journeys, Standard Focus is reducing costs per contact by leveraging bots for easy issues and using humans for complex situations. The result is customer trust and more revenue.
  • Rising CX Superstar. Emily Stubbs, director of Customer Experience, Aerflo. Stubbs has focused on funneling customer experience data into business intelligence tools to build views that head off customer issues before they happen. The proactive approach is critical to product launches and the customer experiences associated with them.
  • CX for Transformation. Virginie Nowak, group chief customer experience officer, Access Bank PLC. Nowak implemented a broad customer experience transformation that has delivered returns across a bevy of metrics. Now Nowak is looking to future-proof customer experience so the bank can double the number of people it serves.
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Google Cloud Vertex AI updates focus on the practical with Context Caching, grounding services

Google Cloud updated Vertex AI with new models, context caching, provision throughput and a bevy of grounding updates with Google Search, third party data and an experimental "grounding with high-fidelity mode."

The Vertex AI enhancements were detailed by Google Cloud CEO Thomas Kurian in a briefing. Kurian's briefing highlights Google Cloud's cadence of Vertex AI updates from Google Cloud Next to Google I/O to those latest additions.

Kurian highlighted customers including Uber, Moody's and WPP leveraging Vertex AI and generative AI. Google Cloud has been touting the 2 million token context window for Gemini 1.5 Pro as well as the performance of Gemini 1.5 Flash. Gemini 1.5 models are generally available.

While touting its own models, Google Cloud, which is on a $40 billion annual revenue run rate, is also emphasizing choice as Kurian noted that Anthropic's Claude Sonnet 3.5 as well as new open-source models such as Mistral and Gemma 2 are available. Google Cloud also launched Imagen 3.

While models are nice, the Vertex AI updates outlined by Kurian really revolve around features that are aimed at enterprises that want to scale generative AI.

Kurian said Context Caching should lower costs for enterprises since you won't have to feed context into the model on each request. Kurian said:

"By introducing a context cache, you only need to give the model the input prompt. You don't have to feed in the context on each request. This is obviously super helpful in lowering the cost of input into the model. It becomes particularly helpful if you've got a long context window and you don't want to keep feeding that long context every time. It is also helpful in applications like chain of thought reasoning, where you want the model to maintain the context rather than must feed it and on every request. So that's a big step forward."

A live demo of Context Caching highlighted how you could analyze the Google Cloud Next keynote with Gemini 1.5 Flash and put together video clips and summaries designed for particular roles such as developers and CIOs.

A few key points about Context Caching:

  • Data is in memory based on customer settings.
  • Customers have two flavors with Context Caching--one based on how much you want to cache and another based on duration and time. 
  • With Context Caching, Google Cloud can more easily leverage its larger context windows in models.
  • Context Caching can reuse content for multiple prompts and lead to a 75% savings in cost and performance.
  • Behind the scenes Context Caching is maintained in Google Cloud VPC for data residency and isolation.

Provisioned Throughput is another addition to Vertex AI. Provision Throughput is designed to provide better predictability and reliability in production workloads. Customers can "essentially reserve inference capacity," said Kurian.

"Customers can still use pay as you go, but if they want to reserve a certain amount of capacity for running a large event or a big ramp of users platform customers can reserve capacity for a time," said Kurian, who said social media companies are using Provisioned Throughput. Snap is a big Google Cloud customer. Customers can use Provisioned Throughput to use new models when generally available or to get assurance on service levels and response times.

On the grounding front, Google is taking multiple approaches where it can leverage third party data and Google Search for timely prompts. The third-party grounding service will include data providers such as Moody's and Thomson Reuters.

Grounding with high-fidelity mode is an experimental feature that includes a grounding score as well as a source. Kurian highlighted an example of a prompt asking about Alphabet's first quarter revenue and an answer with a grounding score. If the question was about Alphabet's third quarter 2024 earnings, the system looks at the context and notes that the quarter hasn't happened yet.

Kurian said:

"High-fidelity grounding is not just a feature of the grounding service. It's a feature of the model itself. The model has been adapted to provide more factuality in its response. In order to do that, the longer context window helps, because you can tell the model to pay attention to what I'm giving you on the input context, and don't get distracted by other things."

Customer use cases

Nick Reed, Chief Product Officer at Moody's, said Google Cloud's grounding features are enabling his company to scale generative AI into production. "Grounding gives us an ability to be able to pair the power of LLMs with knowledge and as proprietary owners of knowledge facts and data," said Reed. "The ability to be able to combine those two things together empowers our customers to be able to use the outputs of the generative AI calls that we're building in actual decision-making processes. We're moving out of the experimental phase into a much more production and decision phase."

14 takeaways from genAI initiatives midway through 2024

Reed said the plan for Moody's is to use Google Cloud's grounding services as a distribution mechanism for its content because end users will be able to trust answers. Reed said:

"It feels like 2023 was the kind of year of experimentation and people were getting used to how this stuff works. Now we're starting to move into a world where we're saying I want to actually use this to drive efficiency in my organization and to be able to use it more directly in decision making and customer touching processes."

Stephan Pretorius, CTO of advertising firm WPP, said Gemini models are being used by the company for speed to market in marketing, which has become a critical KPI for enterprises.

"We use Gemini 1.5 Flash particularly for a lot of the operational automation tasks that we have in our in our business. Everything from brief refinement to strategy development and some ideation concepting tasks," said Pretorius, who said WPP is looking to automate marketing services and its content supply chain.

The WPP CTO added that Context Caching will be critical for the company since "it's not cheap to put 2 million tokens into a query." "If you only have to do that once and you can then cache it, then the entire pipeline of things that you do beyond that becomes a lot more cost effective," said Pretorius.

My take

With its Vertex AI updates, Google Cloud is addressing practical real-life use cases that are evolving from pilot to production. The Gemini 1.5 models have large context windows for bragging rights, but the main effort is to address individual use cases and scenarios.

The big win here is the Context Caching that can drive costs down for enterprises with a close second being the grounding with high-fidelity mode. The first addresses pain points today, but the second may become critical over time since it leverages Google Cloud's key advantage--access to real-time search data.

Kurian said the company is focusing on reducing latency with a family of models and fleshing out techniques like Context Caching that bring costs down. Add it up and what Google Cloud is ultimately building is an abstraction layer that manages context, grounding and other processes all the way down to the GPU and TPU.

More on genAI dynamics:

 

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GenAI will change software pricing models, says Progress Software CEO

Progress Software CEO Yogesh Gupta realizes that generative AI is going to change the way software is priced and his company is experimenting accordingly. One thing is clear: GenAI is going to upend current software pricing models especially those based on seats.

Speaking on Progress Software's second quarter earnings call, Gupta was asked how the company will drive revenue growth with genAI. Progress Software's second quarter revenue fell 2% from a year ago to $175 million, but the company raised its outlook for the year. Progress Software projected fiscal 2024 revenue of $725 million to $735 million with earnings of $1.98 a share to $2.10 a share.

Progress Software is seeing gains as enterprises leverage its data platform and tools for genAI. Gupta's answer was notable only because other software executives aren't as straightforward about it. Enterprise software companies have been talking about the delay in genAI profit euphoria in their most recent quarters. No enterprise is going to pay multiple vendors copilot taxes unless there are returns attached. Progress Software is using AI to add capabilities to its products, drive efficiencies for customers and improve its own processes and operations. Progress Software is using AI internally for technical and customer service, marketing content and customer contract analysis to drive value. 

Here's Gupta's answer in full for context:

 

"I think we in this industry are trying to figure out what is the best way to price our products for the value we are generating. In reality, software pricing has been done by some metric like data consumption, capacity, users, seats or servers. Pricing is based on a measurable quantity. The business value if it is meaningful and significant is often not related to those things.

We are experimenting is the best answer I can give you because I think that is the honest answer. Business models for genAI are going to evolve over the next year or two in our industry. For some products it's easy. Personal productivity is easy. You're Microsoft and you come out with Copilot for Office. Everybody who has Office, if you use copilot, is charged more on a per person basis. We are not like that. This is business value. You might have a fairly small number of users, and you might suddenly see hundreds of thousands or millions of dollars of benefit every year.

That model isn't on a per seat basis, and it isn't on data volume basis. It is truly on the value delivered to the end customer basis. How you tie that value together is really the key question. I wish I had a specific concrete answer for you. I don't other than the fact that we are experimenting as we speak. We are working with customers and others to basically figure out what is the best way to price these things so that they get the value and pay us for the return we're generating for them."

Hats off to Gupta for that answer, which identifies the software industry's biggest conundrum. Enterprise software vendors will need to show growth, but customers are pushing back on the upsell tactics and price increases when the value isn't there yet. Licensing models, subscriptions, pay-per-usage contracts don't account for genAI. That's why there's a rush to lock in customers now before the revenue models change.

For Progress Software, pricing models may be challenging since it has a mix of license, maintenance, subscription and services revenue. The company is a frequent acquirer and recently bought data platform MarkLogic. It also has digital experience, DevOps and infrastructure management software

Indeed, the move from licensing to subscriptions and consumption models typically meant meager growth for 12 to 18 months. This transition to genAI friendly pricing may have a similar time frame.

Meanwhile, enterprises are going to need some budget predictability. Software pricing models with genAI could be more dynamic, personalized and usage based as well as volatile. There may also be models where customers pay based on the value created instead of just access. Those value-based models will create a new set of winners and losers. Value audits will be the new licensing audit for enterprises.

On the buy side of the equation, you can expect generative AI to act as an enterprise advocate by analyzing competition, pricing and bundling and unbundling opportunities. 

Like Gupta, I'm not sure what software pricing models will emerge with genAI. The only certain thing is that the current models don't work. I could see a day where the vendor AI argues with the buyer AI at the negotiating table.

 

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VMware updates VMware Cloud Foundation, adds import features

VMware added a bevy of features to its VMware Cloud Foundation (VCF) platform including import tools that make the migration from vSphere and vSAN to VCF easier.

The updates come as VMware is under fire from customers. When Broadcom completed the VMware acquisition it shifted to subscription-based pricing in a move that raised costs for enterprises.

BT150 zeitgeist: Dear SaaS vendors: Your customers are pissed

Nutanix has been able to add VMware customers, but acknowledged last quarter that Broadcom was responding with aggressive pricing. Hewlett Packard Enterprise also entered the virtualization space by building open-source kernel-based virtual machines into HPE Private Cloud, but that move will take time to play out.

On Broadcom's fiscal second quarter conference call, CEO Hock Tan said that VMware's transition to a new model is on track. VMware revenue in the second quarter was $2.7 billion, up from $2.1 billion in the first quarter. Tan said the company has signed up nearly 3,000 of its largest 10,000 customers to deals, mostly multi-year contracts.

Tan reiterated that VMware would deliver $4 billion a quarter in revenue, but declined to give a time frame.

The VMware Cloud Foundation 5.2 release includes the following:

  • VCF Import from vSphere, vSAN. The import tool enables the integration from vSphere and vSAN into VCF without downtime. With easier migration, VMware can simplify its selling cadence and move customers from point products.
  • VCF Edge, which extends cloud capabilities to edge location and better manage distributed infrastructure.
  • Cloud management enhancements including Tanzu Kubernetes Grid (TKG) as an independent service to manage container-based workloads, a streamlined process to adopt virtual networking and new interfaces for cloud administrators and DevOps.
  • Security features for live VCF patching as well as flexible patch schedules.
  • Broadcom also added new features to VMware vSphere Foundation including self-service tools, TKG and an improved user experience.

Holger Mueller, Constellation Research analyst, said VMware is motivated to move customers to VCF and it's possible that disgruntled enterprises will stick with the company despite competition from Nutanix and possibly HPE. "I expect the same story with VMware as with CA," said Meuller. "There's alarm, disgruntled customers and 85% of enterprises stay. That's a good outcome for tech."

Mueller added:

"So far, Broadcom leadership has shown its first commitment to R&D and innovation. And it is better than what neutral observers were expecting. This innovation now puts VMware customers in the pickle--trust innovation will keep flowing or bet that this update is a one time burst of capabilities. It's up to Broadcom to show a steady cadence of innovation."

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BT150 zeitgeist: Dear SaaS vendors: Your customers are pissed

Enterprise customers are miffed about software-as-a-service vendors trying to double and sometimes triple prices, layering AI-services that may not deliver returns and prioritizing revenue quotas over value.

That's one of the big takeaways from our June BT150 meetup with CxOs.

A few nuggets:

Salesforce has been particularly aggressive about upselling AI and running that cross-selling playbook to the hilt. "We're getting a lot of pressure from Salesforce to buy AI," said one CXO. "Salesforce loves to pitch Data Cloud and anything with data also requires MuleSoft. They're trying to tie it all together which is what I would do if I were them too, but it's very apparent they see AI as a threat and want to lock their customer base in." This sales practice shouldn't be that surprising given Salesforce's goal is to cross-sell you clouds to continue to grow. 

OutSystems was another vendor that was dinged by our CxOs. When the OutSystems contract was up, one CxO was told by sales rep his price would triple. After some back and forth, the solution was apparent to the enterprise customer. Get a new vendor. "These vendors are just coming up with insane things when the contracts expire," he said.

Workday, Adobe and a bevy of others were also called out for similar tactics. Some vendors will play ball and see the win in a long-term relationship and others won't. And we've previously documented the VMware and SAP angst.

BT150 2024:

What is going on here? A few thoughts on why CxOs are increasingly annoyed with their software vendors, which appear to be aggressive.

  • The value provided by the software is mostly horizontal and not necessarily differentiating to the customer's industry. The copilot use cases beyond coding and haven't delivered scalable value just yet. Nevertheless, SaaS vendors are under pressure to show they are monetizing generative AI.
  • Software vendors are playing the annual contract value (ACV) game, but customers want to cut budget. Vendors are happy to sell you more stuff (even if it won't be used) so they can show growth. Customers are looking to hold the line on enterprise IT spending or cut to fund more interesting projects.
  • The margin compression is just starting for software vendors and they can smell the upheaval. My hunch is that terms like "elongated sales cycles"
  • Enterprise buyers want to consolidate vendors and standardize contracts, but not at the expense of lock-in.
  • AI is more of a threat to software vendors than a turbocharger. When you buy SaaS you're getting easier upgrade cycles, more innovation and a consumption model. In many cases, you're also getting a UI. What happens when the UI becomes a natural language generative AI bot? Suddenly the enterprise vendors that grew by relegating rivals to plumbing suffer the same fate.
  • There's little competition right now. Enterprise software is the land of giants and smaller startups that aren't ready to scale. As a result, the bench looks thin, and vendors are looking to press their advantage.
  • It's unclear how this plays out, but some CxOs are leaning toward build over buy. Others are plotting their escapes from overzealous vendors. The real game may not play out for 2 years or so when a) generative UI upends the SaaS market; b) new entrants smell the opportunity to disrupt incumbents.

One thing is clear: No software vendor is going to see ACV going up without delivering value and lowering customer costs. A vendor's ACV chart in an earnings report isn't the enterprise buyer's problem.

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