AI and automation shift from buzzwords to five-year strategy
Late-2025 surveys signal a clear direction: boards and IT leaders now treat AI and automation as long-term, strategic plays. In Rimini Street's C-suite study of 4,295 executives, cyber security and risk management lead today's tactical agenda (44%). But over a five-year view, 46% of CIOs and 43% of CEOs prioritise wider automation and AI adoption. Another 35% aim to become genuinely data-driven.
As Constellation Research's R "Ray" Wang put it: "AI is all about exponential efficiency. And it translates to results of 10x faster and 10x better - delivered at 10x cheaper." Ambitious, yes-but the execution hinges on cross-functional alignment, persistent funding, and disciplined delivery.
What leaders are doing right now
- Executing cloud strategies that reduce complexity and improve agility
- Raising cyber security standards while tackling more sophisticated attacks
- Maintaining compliance amid tighter regulation
- Optimising IT spend as budgets tighten
These are tactical moves. Necessary to stay operationally sound today-and to create room for larger bets tomorrow.
Where the next five years are headed
- Automation and AI at scale: The top long-term priority for CIOs and CEOs
- Data-driven decisions: Building unified data foundations and analytics muscle
- Business continuity: More resilient architectures and processes
- Internal skills: Developing workforce capabilities to execute and sustain change
ROI and the funding reality
Executives expect roughly 27% of payback in years one to two, 37% by years three to five, and full return after six years. That timeline reflects a shift from short-term wins to durable impact-and the need for cost predictability.
Rimini Street CFO Michael Perica notes a stricter investment lens: measurable results, faster payback where possible, and flexible budgeting. His advice: build a "business-driven enterprise software roadmap" that lets leaders reallocate from low-value activities to higher-yield initiatives like agentic AI-improving efficiency, resilience, and long-term growth.
Practical actions for your roadmap
- Align the C-suite on a single AI vision, success metrics, and funding model
- Stand up an AI platform team to centralise guardrails, data access, and reuse
- Prioritise 3-5 automation use cases with line-of-business sponsors and P&L impact
- Modernise data pipelines; treat data quality as a product with clear ownership
- Stage investments: quick wins in 6-12 months, scale plays over 24-60 months
- Bake in security, privacy, and compliance from day one-no exceptions
- Adopt an experimentation portfolio: test, measure, retire or scale-quarterly
- Track value by unit cost, cycle time, error rate, and revenue impact-not vanity metrics
Skills are the constraint-plan for it
Deloitte's latest CFO study finds UK finance leaders expect digital and AI investment to rise over five years, but they don't expect immediate productivity jumps. Only 10% plan near-term spend on training; 73% plan to invest in workforce skills over five years. That gap will slow execution unless addressed now.
As Deloitte UK CEO Richard Houston notes, the upside comes from pairing human capability with AI-and upskilling so nobody gets left behind. See Deloitte's CFO Survey for context: Deloitte CFO Survey.
If you're building skills pipelines by role, explore curated paths: AI courses by job and a focused credential for automation leaders: AI Automation Certification.
How to secure executive buy-in
- Frame every AI initiative in business terms: revenue lift, margin, risk reduction
- Use staged funding with clear exit/scale criteria per quarter
- Tie incentives to delivered outcomes, not project milestones
- Create a shared scorecard across finance, tech, and operations
The bottom line
AI and automation are five-year commitments, not side projects. Win the present with cloud, cyber, compliance, and cost discipline. Build the future with a unified AI vision, a data foundation that actually serves the business, and a skills engine that keeps pace with your ambition.
Set expectations on ROI timing, protect time and budget for experimentation, and double down where the data proves it. Do that, and the "10x" promise becomes less of a slogan and more of a scoreboard.
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