Two to three decades ago, every department had its own IT budget, servers, and support staff. The result was expensive chaos—until smart companies centralized everything into shared service centres. With AI on the rise, history is starting to repeat itself.
The playbook that turned IT chaos into business advantage is now transforming AI deployment.
78% of large enterprises are already using AI in business operations(1), but most are making the same mistakes they made with IT twenty years ago. Different departments are buying different AI tools, creating security nightmares and cost overruns that Gartner predicts will kill 40% of AI projects by 2027.(2)
The companies getting AI right are those applying the shared services playbook: centralized governance, standardized platforms, and federated delivery. That’s more than smart strategy—it’s survival.
The shared services lesson every CEO should remember
Microsoft’s approach proves the model works. Their Copilot Studio now serves 160,000+ organizations with over 400,000 custom AI agents(3). But here’s the key: it operates exactly like a traditional shared service centre—standardized infrastructure with customized delivery.
What made shared services successful?
- Cost efficiency: One platform serving multiple business units
- Risk management: Centralized security and compliance
- Scale advantages: Expertise concentrated, then distributed
Manufacturing giant Siemens has also demonstrated that this works for AI. By centralizing their AI governance while allowing local customization, they achieved a 20-40% reduction in production incidents(4) across global operations. Same principle, different technology.
The economics that will make your CFO smile
This of course very quickly gets interesting for your budget. Companies are spending $1M+ annually on AI initiatives(5), but the ones following shared services principles are seeing returns of 152% on current investments(6).
The secret isn’t spending more—it’s spending smarter. Instead of letting each department buy point solutions, successful companies invest in three phases:
- Foundation (40% of budget): Build the infrastructure once, use it everywhere
- Scale (50% of budget): Deploy across functions with standardized processes
- Innovation (10% of budget): Competitive differentiation on a stable platform
The payoff is obvious. AI systems built this way deliver 50-70% lower maintenance costs than scattered implementations, with breakeven in 18-24 months(7).
Security that doesn’t keep you awake at night
If you think managing employee access is complex, wait until you see what happens when AI agents start multiplying. According to VentureBeat, large enterprises will manage over one million (!!!) AI identities within three years(8) —each potentially accessing sensitive data and systems.
A scattered approach to agentic AI is a security nightmare. Every department buying different AI tools means different security standards, different access controls, and different compliance frameworks. It’s the IT chaos of the 1990s, all over again.
Smart companies are now getting ahead of this by treating AI agents like employees: unique identities, role-based access, and continuous monitoring. 53% of organizations already cite data privacy as their biggest AI obstacle(9). So, companies solving this early will have a massive competitive advantage.
What the winners are doing differently
Retail leaders like Lindex are using centralized AI platforms to analyze trends in real-time, reducing product failure rates and response times from days to minutes (10). Technology companies like Jamf achieved 70% employee adoption of their AI assistant by building on enterprise platforms rather than cobbling together point solutions (11).
The pattern is consistent: companies that treat AI like shared services see faster adoption, lower costs, and better outcomes.
Your 90-day action plan
If you’re a CEO or senior leader, here’s what to do immediately:
- Step 1: Audit every AI initiative in your organization. You’ll probably find more than you expect.
- Step 2: Establish an AI governance committee with representation from IT, legal, and business units. Make someone accountable.
- Step 3: Choose an enterprise AI platform and start consolidating. Don’t let departments continue buying their own solutions.
The companies that moved early on shared services dominated their industries for the next decade. The same opportunity exists with AI—but the window is closing fast.
To sum it up
AI will transform your business, whether you manage it strategically or let it grow chaotically. The difference between AI as a competitive advantage and AI as an expensive headache is the shared services model. The choice is yours: lead with strategy, or follow with regret.
References
- McKinsey & Company – “The state of AI: How organizations are rewiring to capture value”
https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai - Reuters – “Over 40% of agentic AI projects will be scrapped by 2027, Gartner says”
https://www.reuters.com/business/over-40-agentic-ai-projects-will-be-scrapped-by-2027-gartner-says-2025-06-25/ - Microsoft – “Microsoft Build 2025: The age of AI agents and building the open agentic web”
https://blogs.microsoft.com/blog/2025/05/19/microsoft-build-2025-the-age-of-ai-agents-and-building-the-open-agentic-web/ - Computerworld – “Real-world use cases for agentic AI”
https://www.computerworld.com/article/3968681/real-world-use-cases-for-agentic-ai.html - PYMNTS – “CFOs Move AI From Science Experiment to Strategic Line Item”
https://www.pymnts.com/artificial-intelligence-2/2025/cfos-say-enterprise-ai-is-maturing-from-experiment-to-infrastructure - PagerDuty – “2025 Agentic AI ROI Survey Results”
https://www.pagerduty.com/resources/ai/learn/companies-expecting-agentic-ai-roi-2025/ - ai – “ROI of Implementing Agentic AI in Enterprise IT: Metrics That Matter”
https://swish.ai/roi-of-implementing-agentic-ai-in-enterprise-it-metrics-that-matter/ - VentureBeat – “Identity becomes the control plane for enterprise AI security”
https://venturebeat.com/security/identity-becomes-the-control-plane-for-enterprise-ai-security/ - Kiteworks – “AI Agents Are Advancing—But Enterprise Data Privacy and Security Still Lag”
https://www.kiteworks.com/cybersecurity-risk-management/ai-agents-enterprise-data-privacy-security-balance/ - SymphonyAI – “The ultimate use case for agentic AI in retail”
https://www.symphonyai.com/resources/blog/retail-cpg/use-case-agentic-ai-retail/ - Moveworks – “6 Agentic AI Examples and Use Cases Transforming Businesses”
https://www.moveworks.com/us/en/resources/blog/agentic-ai-examples-use-cases