Future-Proofing AI Deployment – Strategy, People and Platforms (Part 3 of 3)

Building the AI-Ready Organisation

People and Skills Over Platforms

Despite the obsession with AI platforms, the long-term differentiator remains people. An AI deployment is only as effective as the team behind it. Upskilling must go beyond data science—it must include product managers, operations staff, and even board members.

At several organisations I’ve advised, we've run “AI fluency” programmes—empowering staff to understand the impact of machine learning on their roles and enabling leaders to question AI outcomes intelligently.

Transformation succeeds when employees evolve from tech users to AI collaborators.

Strategic Technology Foundations

The Role of Cloud, Data and Interoperability

Without cloud-native architecture and strong data governance, AI deployment will stall. Organisations need unified data layers, robust APIs, and scalable platforms.

Key building blocks include:

• Hybrid cloud environments (Azure, AWS, GCP)

• Centralised data lakes for cross-functional intelligence

• Interoperable systems that allow AI to interact across CRM, ERP, and SCM solutions

During my work with FitFlop and Northumbrian Water, we implemented data governance frameworks and migrated legacy infrastructure, enabling AI engines to scale and deliver consistent value across geographies.

The Boardroom Agenda: AI as a Business Strategy

AI is no longer just a CIO priority—it’s now central to corporate strategy. Boards are demanding a clear line from AI investment to EBITDA impact. CIOs and transformation leaders must respond with:

• Strategic AI roadmaps

• Business-aligned KPIs

• Clear ROI projections

Advisory boards increasingly expect CIOs to articulate how AI supports market expansion, customer intimacy, and operational agility.

Closing Thoughts

The era of high-volume AI experimentation is over. What lies ahead is a new standard of precision, accountability, and transformation.

To thrive, businesses must embed AI into their operational DNA, governed by strategy, executed by skilled teams, and underpinned by adaptive platforms.

Those who lead this shift won’t just deploy AI—they’ll reshape their industries with it.

FAQs

What is outcome-driven AI deployment?

It’s an AI strategy focused on measurable business results—such as cost reduction, revenue growth, or operational efficiency—rather than experimentation.

How do you embed AI into a business?

By aligning it with ERP, CRM, and cloud platforms, backed by data governance and strategic oversight.

What are the biggest challenges in AI deployment?

Poor data quality, lack of business alignment, skills gaps, and inadequate governance are the most common hurdles.

Richard Keenlyside is a Global CIO, PE&MA Advisor, Endava TAC and a former IT Director for J Sainsbury’s PLC.

Call me on +44(0) 1642 040 268 or email richard@rjk.info.

Follow me on X https://x.com/cioinpractice & LinkedIn https://www.linkedin.com/in/richardkeenlyside/