Assessment of AI Adoption and Diffusion in Organizations Across Industries
Situation
Our client was looking for primary research to support a new thought leadership on Data & AI, specifically how AI is getting adopted and diffused in organizations.
Objective
The objective was to explore how organizations can effectively adopt and scale AI while reinventing industry-specific processes to unlock new potential and enhance performance through Generative AI.
Our Work
10EQS conducted interviews with senior executives at organizations across industry verticals globally to assess their Gen AI maturity and adoption, investment strategies, integration within industry contexts, and partnership strategies to augment capabilities. 10EQS also explored the planning for effective Generative AI adoption, value creation, and strategies for overcoming related challenges.
Project Team
- Ex-Deloitte Management Consultant with extensive experience in GenAI and technology transformations, and developing thought leadership research
- 10EQS Delivery Operations (=PMO) providing quality assurance, process management and expert recruitment
- 22 industry experts
Industry experts (excerpt)
- Chief Data Officer – Public Sector Organization (US)
- Distinguished Scientist and Director AI – Technology & Communications Company (India)
- Head of AI Security – Consumer Goods Company (UK)
- IT Chief Data Officer for Procurement & Supply Chain – Utilities Company (Netherlands)
- Vice President of Digital – Retail Company (China)
- SVP of Technology and Digital/Data/AI/IoT Transformation – Energy & Utilities Company (US)
- Director of Data Strategy, Data Science and AI – Life Sciences Company (UK)
Results
10EQS found that the primary desired outcomes for Gen AI are to enhance efficiency, drive revenue growth, and improve decision-making processes. To assess the value of Generative AI initiatives, they establish clear success metrics, perform ROI assessments, and track key outcomes such as productivity and customer satisfaction, ensuring that pilot programs align with overall business objectives.
While some organizations are starting to see lower-than-expected value creation, they are adopting a greater focus on the path to value. Gen AI maturity varies across industries and organizational operating models. Leading organizations are developing core capabilities to enable gradual non-specific GenAI solutions while focusing on innovative solutions to “core” industry challenges to drive differentiation.
Gen AI Maturity:
- High: Financial Services, Life Sciences & Healthcare, Energy, Manufacturing, Utilities & Industrials
- Moderate: Retail and Consumer Goods, Media
- Low: Telecom, Public Sector
Investment Trajectory:
- High: Financial Services, Retail and Consumer Goods, Telecom, Media
- Moderate: Life Sciences & Healthcare
- Low: Energy, Manufacturing, Utilities & Industrials, Public Sector
Other themes explored include use case origin, resource alignment, value tracking maturity, governance and operating model, data accessibility, and internal expertise and training.