A COMMISSIONED STUDY CONDUCTED BY FORRESTER CONSULTING ON BEHALF OF BAKER HUGHES AND C3.AI, OCTOBER 2024 The State Of Generative AI In Heavy Industries Energy, Chemicals, And Heavy Manufacturing Companies Are Prioritizing GenAI To Drive Operational Improvements Across Their Value Chain
Executive Summary Baker Hughes, in partnership with C3.ai, commissioned Forrester Consulting to evaluate the state of generative AI (genAI) at enterprises in “heavy industries,” specifically those in energy/utilities, heavy manufacturing, and chemical manufacturing sectors. We found that accelerating their organization’s ability to harness genAI is a high priority for decision-makers in these industries who aspire to use it to drive improvements across a variety of scenarios. Yet most of these decision-makers are struggling to keep up with genAI’s rapid evolution. Many are collaborating with partners to source needed capabilities so they can swiftly and securely move from experimentation to innovation. ABOUT FORRESTER CONSULTING Forrester provides independent and objective research-based consulting to help leaders deliver key outcomes. Fueled by our customer-obsessed research, Forrester’s seasoned consultants partner with leaders to execute their specific priorities using a unique engagement model that ensures lasting impact. For more information, visit forrester.com/consulting. © Forrester Research, Inc. All rights reserved. Unauthorized reproduction is strictly prohibited. Information is based on best available resources. Opinions reflect judgment at the time and are subject to change. Forrester®, Technographics®, Forrester Wave, and Total Economic Impact are trademarks of Forrester Research, Inc. All other trademarks are the property of their respective companies. [E-61332] Project Team: Sophia Christakis, Market Impact Consultant Contributing Research: Forrester’s Technology Architecture & Delivery research group © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED. 2 3
GenAI Smooths The Friction Between Humans And Technology GenAI represents a set of technologies and techniques that leverage massive corpuses of data — including large language models (LLMs) — to generate new content (e.g., text, video, images, audio, code) using natural language prompts or other noncode/nontraditional inputs.1 GenAI promises to transform how enterprises operate, employees do their jobs, and consumers interact with brands.2 “How is your organization using or interested in using genAI to drive transformation and impact?” “Generate prioritized inspection routes and protocols based on risk assessments” C-LEVEL EXECUTIVE, ENERGY/UTILITIES “Automate quality control processes by analyzing sensor data” VICE PRESIDENT, HEAVY MANUFACTURING “Collect data from sensors, equipment, and production parameters for enhancing our chemical processes” C-LEVEL EXECUTIVE, CHEMICAL MANUFACTURING “Create simulations that allow us to shift into cleaner energy sources” DIRECTOR, ENERGY/UTILITIES “GenAI presents a new wave of transformation and disruption in my organization’s industry.” 73% agree 5 © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED. 4 Base: 96 leaders in North America with authority or influence over AI and/or analytics decisions at energy/utilities, heavy manufacturing, and chemical manufacturing organizations Source: A commissioned study conducted by Forrester Consulting on behalf of C3.ai, February 2024
GenAI Will Soon Be Ubiquitous Many heavy industry organizations are moving aggressively from genAI exploration to adoption. Sixty percent of these leaders come from organizations that are already using or piloting genAI. GenAI Adoption And Interest Is Growing Rapidly Currently piloting Planning to use within 12 months Planning to use in 13 to 24 months 45% 15% 17% 11% 88% Currently using will adopt genAI within two years. 7 6 © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED. Base: 96 leaders in North America with authority or influence over AI and/or analytics decisions at energy/utilities, heavy manufacturing, and chemical manufacturing organizations Source: A commissioned study conducted by Forrester Consulting on behalf of C3.ai, February 2024
Leaders Are Drawn To A Variety Of GenAI Use Cases Heavy industry leaders aspire to use genAI to drive improvements for business-critical requirements including efficiency, reliability, sustainability, and compliance scenarios: • Research and development (e.g., accelerate product development, improve research processes, develop predictive modeling, perform simulations). • Operational reliability (e.g., surface operational risks, optimize asset performance, enhance maintenance troubleshooting, improve safety). • Process/energy optimization (e.g., increase production throughput, ensure quality, optimize process efficiency, reduce resource costs). • Supply chain (e.g., improve network visibility, streamline supplier management, improve order fulfillment). • Environmental, social, and governance (ESG) (e.g., improve sustainability performance, ensure reporting compliance, drive stakeholder engagement). Current And Near-Term GenAI Use Case Adoption 29% 23% 14% Research and development 24% 22% 17% Operational reliability 13% 32% 16% Process and energy optimization 18% 25% 17% Supply chain 11% 23% 17% ESG Currently using Currently piloting Planning to use within the next 12 months are interested in, planning to use, or already using genAI for these use cases. More than 75% 9 © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED. 8 Base: 96 leaders in North America with authority or influence over AI and/or analytics decisions at energy/utilities, heavy manufacturing, and chemical manufacturing organizations Source: A commissioned study conducted by Forrester Consulting on behalf of C3.ai, February 2024
Pressure To Harness GenAI Is Mounting Seventy-three percent of heavy industry leaders describe accelerating the ability to harness genAI as a high priority for their organization. Meanwhile, broad confusion about and misunderstanding of genAI persists. Leaders are bombarded with near-daily announcements of new features, investments, and partnerships.3 Understandably, many decision-makers struggle to keep up. “How much do you agree or disagree with the following statements?” “Accelerating the ability to harness genAI is a high priority for my organization.” 73% agree “My organization struggles to keep up with the rapid pace genAI is evolving at.” 63% agree 11 © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED. 10 Base: 96 leaders in North America with authority or influence over AI and/or analytics decisions at energy/utilities, heavy manufacturing, and chemical manufacturing organizations Source: A commissioned study conducted by Forrester Consulting on behalf of C3.ai, February 2024
Barriers Stand In The Way Of GenAI Ambitions A shortage of in-house expertise means heavy industry decision-makers lack the ability to remedy a host of common genAI obstacles, including difficulty deploying and scaling early prototypes, integrating with existing infrastructure, and developing a clear strategy. These issues make it hard to build strategic momentum around early genAI successes. Top GenAI Barriers Challenges Hinder GenAI Adoption And Expansion Decision-makers understand that addressing top genAI challenges is necessary to capitalize on genAI opportunities while protecting against any negative outcomes. To date, just 42% of early adopters have scaled genAI beyond the individual or team level. Likely Consequences Of Failing To Adequately Address GenAI Challenges Eroded experiences 46% Security and compliance risk 40% Limited repeatability and scalability 32% PEOPLE- OR PROCESS-RELATED DATA- OR TECHNOLOGY-RELATED Difficulty deploying and scaling early prototypes 50% Difficulty integrating with existing infrastructure 44% Shortage of in-house genAI expertise 48% Lack of enterprise tools to work with the models 43% Lack of a clear genAI strategy 41% Data security concerns 43% Difficulty identifying genAI use cases in my organization’s business 40% Inadequate data strategy 40% 13 © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED. 12 Base: 96 leaders in North America with authority or influence over AI and/or analytics decisions at energy/utilities, heavy manufacturing, and chemical manufacturing organizations Source: A commissioned study conducted by Forrester Consulting on behalf of C3.ai, February 2024 Base: 96 leaders in North America with authority or influence over AI and/or analytics decisions at energy/utilities, heavy manufacturing, and chemical manufacturing organizations Source: A commissioned study conducted by Forrester Consulting on behalf of C3.ai, February 2024
GenAI’s Importance Will Continue To Expand Rapidly Heavy industry leaders expect genAI’s importance to grow even more in the coming years, underscoring the value of keeping up with genAI innovation. Now is the time to experiment with internal use cases and build AI muscles to avoid being blindsided by developments or disruptions.4 “How important, if at all, is genAI to your organization’s work today and in the future?” Importance to my organization’s work today Importance to my organization’s work in 13 to 24 months Importance to my organization’s work in 12 months Very important Important Decision-makers expect 39% of their employees to be using sanctioned genAI for work by the end of the year, on average — a 26% increase in 12 months. 46% 20% 66% 89% 42% 47% 72% 33% 39% 15 © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED. 14 Base: 96 leaders in North America with authority or influence over AI and/or analytics decisions at energy/utilities, heavy manufacturing, and chemical manufacturing organizations Source: A commissioned study conducted by Forrester Consulting on behalf of C3.ai, February 2024
Users Are Already Benefiting From GenAI Despite being in the early stages of their adoption, more than 50% of genAI users from heavy industries have already realized revenue, operational efficiency, and customer experience improvements from genAI. Top Improvements GenAI Users Have Realized Or Expect “GenAI is a key driver for efficiency improvements and process optimization.” C-LEVEL EXECUTIVE, ENERGY/UTILITIES “ Customer experience 44% 95% 51% Revenue growth 35% 91% 56% Employee experience 40% 84% 44% Cost efficiency 51% 93% 42% Operational/process efficiency 37% 89% 53% Rapid access to institutional knowlege 42% 91% 49% Ability to accelerate new product/service development 39% 81% 42% Improvements already realized Improvements expected 17 © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED. 16 Base: 57 leaders in North America with authority or influence over AI and/or analytics decisions at energy/utilities, heavy manufacturing, and chemical manufacturing organizations that are currently using or piloting genAI Note: Showing top responses; individual percentage values may not sum to totals due to rounding. Source: A commissioned study conducted by Forrester Consulting on behalf of C3.ai, February 2024
Partners Are Powering GenAI Strategies Given the pressure on decision-makers to accelerate genAI capabilities in a complex landscape and a lack of requisite skills internally, partners have an important role to play. Leaders at heavy industry organizations that have adopted genAI are more likely to leverage partners than internal resources to execute their genAI strategies. Currently, leaders are focused on using partners to deploy readily available genAI applications. Leaders are drawn to a range of partner types, especially AI application providers, as well as agency, services, and consulting partners. Most Enterprises Will Buy — Not Build — GenAI “My organization would prefer to buy prebuilt applications designed for the needs of its industry.” 71% agree 67% view external partners as critical to their organization’s ability to harness genAI quickly and effectively. 19 18 Base: 96 leaders in North America with authority or influence over AI and/or analytics decisions at energy/utilities, heavy manufacturing, and chemical manufacturing organizations Source: A commissioned study conducted by Forrester Consulting on behalf of C3.ai, February 2024 © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED.
Leaders Prioritize Partners That Understand Their Industry To produce relevant results and drive differentiated value from genAI, heavy industry organizations need genAI solutions that are secure, grounded in enterprise-specific data, and connected to customer and employee workstreams. Decision‑makers value partners that can support these goals. “Experience in industry AI app development significantly accelerates genAI deployments, given experience in codifying business processes.” 62% agree The Five Most Important Criteria When Evaluating GenAI Partners 60% believe generic LLMs fall short in addressing their organization’s industry- and domain-specific needs. Experience in industry AI application development 55% Full enterprise access controls and security 48% Experience with domain‑specific use cases 44% Experience with codifying business processes 45% Support for diverse types of industry-specific data 44% 21 © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED. 20 Base: 96 leaders in North America with authority or influence over AI and/or analytics decisions at energy/utilities, heavy manufacturing, and chemical manufacturing organizations Source: A commissioned study conducted by Forrester Consulting on behalf of C3.ai, February 2024
Conclusion Work with proven partners with heavy industry domain expertise during your genAI adoption journey. The world of genAI technologies is evolving fast — far faster than most enterprises can keep up with. Enterprises are turning to partners to accelerate AI journeys, but with so many new companies entering the market, it is critical to work with trusted and proven partners that understand your specific heavy industry challenges. Build future-fit genAI success with a concerted and flexible strategy. Enterprises that are not deliberate about their organizational and data strategies risk falling behind or worse — increasing organizational hesitancy about AI. Enterprises must maintain flexibility in their technological approach to effectively evolve their applications and architectures to meet the rapid pace of innovation in this space. People are the crucial factor in genAI success. Organizations cannot expect to successfully roll out genAI use cases without significant efforts toward preparing the organization and change management. GenAI applications today are often assistive tools, but employees and teams need close support to ensure they adopt them and extract maximum value. Methodology In this study, Forrester conducted an online survey of 96 AI and analytics decision-makers at energy/utilities, heavy manufacturing, and chemical manufacturing organizations in North America. The study began in January 2024 and was completed in February 2024. Endnotes 1 Source: Generative AI: The Top Six Things Tech Executives Need To Know, Forrester Research, Inc., April 17, 2023. 2 Source: The State Of Generative AI, 2024, Forrester Research, Inc., January 26, 2024. 3 Source: Ibid. 4 Source: Ibid. COUNTRY United Sates 56% Canada 44% Note: Percentages may not total 100 due to rounding. Demographics INDUSTRY Energy/utilities 67% Heavy manufacturing 21% Chemical manufacturing 13% ANNUAL REVENUE (USD) $2B to less than $3B 38% $3B to less than $4B 23% $4B to less than $5B 24% $5B or more 16% SENIORITY C-level executive 15% Vice president 32% Director 53% 23 © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED. © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED. 22
Explore More RELATED FORRESTER RESEARCH The Generative AI Advantage, Forrester Research, Inc., November 29, 2023 Generative AI: The Top Six Things Tech Executives Need To Know, Forrester Research, Inc., April 17, 2023 The State Of Generative AI, 2024, Forrester Research, Inc., January 26, 2024 CONTACT BAKER HUGHES © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED.
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