This is the first in a two-part AI series from Eleanor Dempsey, Auxilion’s Director of Strategy, Innovation and Transformation.
AI: From Paradox to Profit and Why Governance Matters
I have to admit, I have approached the conversation around AI with a healthy dose of scepticism. Like many of us, I have seen the flood of articles promoting its transformative power. Yet the reality for most businesses has been a mix of promising pilots and a perplexing lack of tangible impact. Everyone seems to have experimented with chatbots and copilots, but where is the real, lasting value?
For our clients, this question is critical. The stakes are too high for experimentation without a robust framework. They have made it clear that unless an AI solution is enterprise grade, built with governance, risk and compliance at its core, they are simply not interested. This is the lens through which we must view AI, especially with the phased arrival of the EU AI Act.
The Acceleration of AI Adoption
AI has been around for years, but the current wave of interest is reminiscent of the cloud computing boom of the 2010s. The key difference this time is the speed and breadth of consumer adoption. With cloud, the shift was primarily enterprise-led, a gradual migration of data centres and applications. AI, however, is reaching consumers directly through handheld devices and everyday applications.
Research from Eurostat indicates that the percentage of enterprises in the EU using AI grew from 8% in 2023 to 13.5% in 2024, a rapid rise that is driving both opportunity and pressure. This swift exposure has created widespread awareness and urgency for enterprises to act quickly, but also responsibly.
Understanding Agentic AI
McKinsey’s latest report, Seizing the Agentic AI Advantage, sheds light on this paradox, suggesting the issue is not with AI itself, but with how it is being used. The answer, they argue, lies in agentic AI.
Agentic AI refers to systems that do not just assist, but act. These autonomous, goal-driven agents can plan, reason, and execute tasks independently to achieve business objectives. It is the difference between a chatbot that helps draft an email and an agent that schedules a client meeting, coordinates with the sales team, and updates the CRM, all without human intervention.
The key to making this shift is to become AI-ready. That means treating these tools not as isolated features, but as integral components of the operational fabric, where use is tightly governed to minimise exposure and maximise impact on profit and loss.
The Risks of Unstructured AI Adoption
On our travels, we have observed a few instances, albeit limited, where the approach to AI adoption has been perhaps overenthusiastic. The mindset has been one of needing to roll out AI licences and apply AI across the board to reduce headcount, without fully considering the broader implications. This can introduce significant risk. This approach often overlooks disruption to workflows, end-user adoption, data governance and security, including the need to ensure the environment is properly ringfenced and permissions are tightly controlled.
A common misconception is that data entered into a public AI tool is somehow private. In reality, unless an enterprise-grade AI solution with defined security and privacy protocols is used, data submitted may be used to train the underlying model. That means confidential business information, including customer data and proprietary internal documents, could be inadvertently shared and potentially exposed.
Even with licensed business AI tools, security depends on the safeguards a business has implemented. These tools typically operate within existing enterprise environments and respect configured permissions. However, if a user has overly broad access to sensitive data, the AI may surface that information, increasing the risk of oversharing or unintended disclosure.
The absence of a robust AI governance strategy can lead to well-documented risks, including biased outputs, breaches of data privacy and compromised model integrity. Unstructured or overzealous adoption can result in serious consequences, including:
- Data leaks where sensitive information is inadvertently exposed through public AI platforms or misconfigured enterprise solutions
- Compliance breaches where insufficient oversight leads to violations of data protection laws such as GDPR with financial and legal repercussions
- Reputational damage where incidents such as breaches or publicly visible AI bias erode customer trust and harm brand credibility
Building a Governance Framework
These risks can be mitigated through a comprehensive AI governance framework developed in collaboration with trusted IT partners. In practice, this means establishing clear policies around data access, usage, and retention, defining roles and responsibilities, embedding ethical guidelines into AI design and deployment, and ensuring continuous monitoring and auditability.
Do Not Forget the Human Factor
Embedding AI into an organisation’s fabric requires a shift in how people work. To realise the productivity gains these technologies promise, end users must be brought on the journey through targeted training, clear communication, and a culture that supports adoption and trust. Governance is not just about security and control, it is about enabling people to use AI confidently and responsibly.
The Opportunity Ahead
McKinsey’s framing of the generative AI paradox reminds us that the real value lies not in the tools themselves, but in how they are embedded into the business. Agentic AI offers a path forward, but only if organisations are prepared to govern it effectively. The shift from experimentation to enterprise grade execution is not just a technical challenge, it is a strategic imperative.
The opportunity is significant. When deployed thoughtfully, AI can unlock new levels of efficiency, insight and innovation across the business. If your organisation is exploring AI adoption and wants to ensure that it is secure, scalable, and strategically aligned, Auxilion’s dedicated advisory team is here to support you.
Through the Auxilion Way, we help clients assess readiness, define governance structures, and embed AI into the operational fabric of the business. From digital strategy and AI and data readiness to change enablement, we can guide you through every step of your AI and data readiness journey.
In part two of this blog, I will explore how AI governance can safely and effectively support a new chapter of innovation and growth for your business. To discuss Auxilion's AI support, contact hello@auxilion.com.
