AI, Governance & Transformation: What Leaders Need to Know in 2025

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12.03.25
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At our latest Leaders in Transformation event, senior executives from a range of industries gathered to discuss the imperatives shaping business transformation in 2025. While AI dominated much of the discussion, the conversation also touched on governance, regulation and how businesses can adapt to a rapidly evolving landscape.

What became clear is that AI is no longer a future consideration—it’s a present-day business reality. Yet, while some organisations are integrating AI effectively, many are still struggling with governance, data quality and understanding AI’s full impact.

Our own Archie Cobb (who we’ve aptly nicknamed AI-chie), a senior AI consultant at Sullivan & Stanley, provided a valuable AI maturity model to help organisations assess where they currently stand. He offered some salient advice: “It’s not just about adopting AI—it’s about structuring it in a way that makes sense for your business. If you don’t have clear policies and a plan, AI will cause more problems than it solves.”

This blog explores the key takeaways from the evening, the challenges businesses need to address, and practical guidance on AI readiness.

AI Governance: From Compliance to Competitive Advantage

One of the strongest messages from the discussion was that AI governance is not optional—it’s essential for risk management, regulatory compliance and business credibility.

A financial services leader highlighted a key risk:

“The biggest issue isn’t AI itself—it’s shadow AI. We have employees using ChatGPT to draft emails, summarise contracts, and generate insights without any oversight. That’s a major problem.”

This is a growing challenge across industries. Without proper governance, AI can introduce risks such as:

  • Shadow AI – Employees using AI tools without company approval or oversight.
  • Hallucinations – AI generating false or misleading outputs that go unchecked.
  • Legal & regulatory breaches – AI-generated content being used without clear contractual terms around liability and data protection.

A legal industry executive reinforced this concern:

“AI-generated content is increasingly being challenged in court. If you don’t have clear contractual terms around liability and data protection, you could find yourself in serious trouble.”

How to take control of AI governance

At S&S, we can offer a structured approach for organisations looking to take control of AI governance before it becomes a liability. Our top considerations are:

  • Create an AI policy and roadmap – Define what AI tools employees can and cannot use. Make it clear how AI outputs should be verified and used responsibly.
  • Establish a governance framework – Set up internal oversight for AI usage, ensuring compliance with existing data protection and security standards.
  • Train your teams – Employees need to understand AI risks, including bias, misinformation and ethical considerations.
  • Monitor AI use continuously – AI policies should evolve as regulations and best practices develop.

Archie emphasised: “Governance isn’t about stifling innovation—it’s about ensuring AI is used safely and effectively. The businesses that get this right will gain a real competitive advantage.”

DRIVING AI TRANSFORMATION IN YOUR ORGANISATION: DO YOU NEED A LEAD

Navigating a shifting regulatory landscape

Another key challenge for businesses is keeping up with evolving AI regulations.

  • The EU AI Act enforces strict compliance and liability rules.
  • The UK and Canada favour principle-based, pro-innovation frameworks overseen by regulators like the ICO and FCA.
  • The US and China are taking diverse but increasingly structured approaches to AI regulation.

A transformation leader in the professional services industry noted:

“We’re already seeing fines issued for AI misuse. Companies that ignore these regulations are taking a huge gamble.”

Steps to stay compliant with AI regulations

  • Stay informed – Assign a compliance lead to track AI regulations in every region where your company operates.
  • Implement transparent AI models – Avoid ‘black box’ Large Language Models (LLMs) that lacks explainability.
  • Document decision-making – If AI is involved in major business decisions, there should be a clear audit trail.
  • Run compliance checks regularly – Review AI outputs and ensure they align with legal and ethical standards.

Much like the example Archie shared, The EU AI Act has stringent penalties for non-compliance, including fines of up to €35 million or 7% of a company’s total worldwide annual turnover for the preceding financial year, whichever is higher.

AI in action and pervasive integration: Real-world use cases and challenges

While governance and regulation are critical, one of the biggest shifts we are seeing that was noted in our discussion is that AI is helping drive a host of strategic initiatives this year. AI is now permeating operations for cost optimisation, customer experience for personalisation and product innovation. It’s not a matter of if businesses will adopt AI—it’s a question of when and how fast.

A transformation director in retail summarised this shift:

“We used to think of AI as something our IT team would manage, but now it’s influencing everything—from customer recommendations to supply chain forecasting.”

This pervasive integration of AI is already visible in several industries:

  • Operations – AI is improving supply chain logistics, optimising inventory, and reducing downtime in manufacturing.
  • Customer experience – AI-powered chatbots, personalised recommendations and predictive support are enhancing customer interactions.
  • Product innovation – Companies are embedding AI into new products and services, such as smart home devices, healthcare diagnostics and financial advisory tools.

Several notable real-world examples delivering significant business impact were discussed:

  • Tesla is using AI to predict supply chain needs six months in advance, reducing waste and optimising logistics.
  • The NHS is applying AI for queue management, helping reduce waiting times in hospitals.
  • A leading insurance firm has cut customer complaint handling times in half by using AI to summarise cases and generate resolution letters.

Every business leader—not just CIOs—needs to be engaged in AI strategy. Organisations should assess which functions can benefit most from AI and create a roadmap for adoption that aligns with business goals.

However, as Archie pointed out, AI is only as effective as the data it’s built on:

“If your data is messy, your AI decisions will be too. Poor data quality is one of the biggest barriers to AI success.”

This sentiment was echoed by a technology leader in the room:

“We’ve automated processes, but bad data still creates errors. AI can enhance decision-making, but only if the underlying data is clean.”

AI readiness: Moving beyond experimentation

Many companies are still at the early stages of AI adoption, with employees using AI tools informally but without a structured approach. To move from ad-hoc usage to strategic AI integration, businesses need to define their value orchestration approach. It is all very well having AI initiatives, but how do you get the board buy in? The value output is just as important as the ideation around the original idea.

We provide a simple AI maturity model to help organisations assess where they stand:

  1. Ad-hoc: Experimenting and researching potential applications for AI​
  2. Nascent: Initial investments in data infrastructure and POCs​
  3. Codified: Integrating AI into core operations and improving AI processes
  4. Governed: AI considered a core competency and critical to operations
  5. Leading: Embedded AI company wide, develops new business models and revenue streams.
AI Maturity Model

“Most businesses are stuck between levels 1 and 2,” Archie explained. “S&S can help you level up. Through a clear roadmap, AI policies, change transformation and informing your data quality.”

The future of AI and business transformation

The event reinforced that AI is not just a technological shift—it’s a fundamental change in how businesses operate.

Organisations that take AI governance seriously, stay ahead of regulation, and integrate AI strategically will gain a competitive advantage. The challenge now is moving from AI experimentation to full-scale adoption—safely and effectively.

Key questions for leaders:

  • Is your AI usage governed effectively?
  • Are you prepared for AI regulation changes?
  • Do you have structured, high-quality data?
  • Where does your company sit on the AI maturity curve?

AI won’t replace leadership—but it will reshape how leaders make decisions, manage risk and drive innovation. The next 12 months will be critical for businesses navigating this transformation.

What’s your biggest AI challenge right now? Let’s continue the conversation.

Ricky Wallace Sullivan & Stanley
Written by Ricky Wallace
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