Our Report TL;DRs serve up a quick look at recently-published reports worth paying attention to, and sharing with your team. Important note: our editorial team and contributors select these. The firms producing these reports don’t pay to be featured.
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Report Title
Now Decides Next: Generating a New Future (PDF version) — Deloitte
Published
January 5th, 2025
Most Useful For
C-Suite, innovation leaders, HR, and change managers
Data Sources
Deloitte surveyed 2,773 leaders from what they called “AI-savvy organizations” between July and September 2024. Respondents were senior leaders at the board, C-suite, VP, and Director levels. The survey was split equally between IT and line-of-business leaders. Fourteen countries were represented.
Key Findings
- Organizational change capacity has put a “speed limit” on adoption
Key Quote: “With transformational technologies, there are always gaps between the pace of technological change and the ability of individuals, businesses and policymakers to keep up. GenAI is no exception.” - Enterprise data curation, cleaning and management is key
Key Quote: “‘Data emerged as the central factor for [our GenAI] success,’ said a former software engineering manager for one of the world’s leading technology companies.” - Bottom-up experimentation is driving progress moreso than top-down mandates
Key Quote: “While the C-suite has been slower to engage in AI implementation, teams across the company are developing proofs-of-concept and driving AI adoption.” - Current GenAI implementations are reaping rewards in efficiency and time savings
Key Quote: “Nearly three-quarters (74 percent) say their most advanced initiative is meeting or exceeding their ROI expectations.” - Bias, hallucination, and inaccuracy are the biggest resistance factors
Key Quote: “For broader GenAI adoption to occur, the technology’s reliability, accuracy, and trustworthiness will need to improve.” Not delivering the expected value is another significant barrier to GenAI adoption (see chart below.) - Future agentic or autonomous, goal-driven systems will pose unique challenges
Key Quote: “The key barriers currently facing GenAI…are arguably even more important and challenging due to the increased complexity of agentic AI systems.”
One Great Chart
Questions to Discuss with Your Team
- How can we shift our focus from technology catch-up to competitive differentiation with GenAI, and what are the key areas of our business beyond IT where we can have the most impact?
- What specific steps can we take to accelerate our organizational readiness in areas like data, risk management, governance, regulatory readiness, and talent?
- As leaders, how can we ensure that our enthusiasm for GenAI gets beyond cheerleading and more towards removing barriers and enabling experiments at scale?
- What are the initial low-risk use cases for agentic AI that we can focus on to test and build our data management, cybersecurity, and governance capabilities?
- How can we establish centralized governance without throttling creative experimentation, so that we continuously iterate on and socialize high value experiments?
