The Real ROI of AI: Beyond the Hype

The AI gold rush is real, but most companies are digging in the wrong places. Having just completed my AI Diploma with Distinction at UCD in 2025, and with 35+ years of IT delivery experience, I've witnessed the gap between AI promise and AI reality.

The problem isn't the technology—it's the approach. Organizations rush to implement ChatGPT integrations or build ML models without asking the fundamental question: "What repetitive, high-cost process can we eliminate?"

Real AI ROI comes from three areas that most consultants won't tell you about because they're not sexy enough to sell:

**Document Processing Automation** Stop paying humans to read invoices, contracts, and forms. Modern AI can extract structured data from unstructured documents with 95%+ accuracy. One financial services client I advised reduced invoice processing time from 3 days to 3 hours—that's a 24x improvement. The AI cost? Less than one FTE salary.

**Intelligent Decision Support** AI doesn't need to make decisions—it needs to surface the right information at the right time. In a recent programme delivery project, we implemented AI-powered risk flagging that analysed project documentation and flagged potential issues 2 weeks earlier than traditional methods. Early detection = lower remediation costs.

**Customer Service Deflection** Everyone talks about chatbots. Few talk about intelligent routing and self-service optimisation. By analysing support ticket patterns with AI, we identified that 40% of customer contacts were asking variations of the same 12 questions. The solution wasn't a chatbot—it was better documentation placement and proactive notifications. AI identified the problem; simple UX changes solved it.

**The Implementation Reality** Here's what 35 years of delivery experience teaches you: technology is 20% of the solution. The other 80% is change management, process redesign, and stakeholder buy-in. AI projects fail when technologists lead them. They succeed when business leaders own the outcomes and technologists enable the execution.

**Your Next Step** If you're considering AI implementation, start with a process audit, not a technology evaluation. Identify your three most expensive repetitive processes. Calculate the fully-loaded cost (salary + overhead + error correction + delays). Then ask: "Could AI reduce this by 50%?"

If the answer is yes, you have a business case. If the answer is no, you're chasing hype.

After 35+ years across banking, insurance, telecommunications, and government sectors, I can tell you this: the best AI project is the one that pays for itself in 6 months. Everything else is a science experiment.