European companies face barriers to AI integration
AI has immense power, endless potential, but takes precision to launch it successfully. Across the UK, France, and Belgium, businesses are beginning to grasp just how game-changing AI can be for their industries. In fact, 72% of IT leaders believe AI will reshape their sector, and 29% are bracing for extreme disruptions. There’s tangible proof that AI is already driving financial gains, with half of all respondents and 70% of senior executives reporting positive impacts on their bottom line. It’s no surprise then that 50% of these companies are gearing up to expand their AI investments.
Optimism isn’t enough to get the job done though. Many companies are finding that embracing AI comes with a steep learning curve. Financial constraints are holding back 14% of businesses, while 12% are tangled up in integration issues, struggling to make new AI systems play nice with their existing infrastructure. Even more telling, 11% admit they don’t have the right strategies in place, and 9% are simply short on skilled personnel.
The ambition is there—companies want to use AI to streamline operations, cut costs, and drive innovation. The problem is that many aren’t ready for the realities of implementation. They’re like early explorers charting new territory without a clear map. The opportunities are massive, but the challenges demand clear planning and focused action.
Ethical considerations in AI deployment lack actionable frameworks
Ethics in AI the compass that guides responsible innovation. And while many European businesses seem to understand this concept, their actions suggest otherwise. A surprising 63% of companies say ethics are “very” to “extremely” important in their AI strategies, yet 44% lack even basic ethical guidelines. Even fewer (just 28%) have tools in place to address ethical dilemmas.
And it gets worse. Workforce preparation, a core of ethical and effective AI, is being ignored by 40% of companies. No training, no upskilling, no plans. This leaves them vulnerable to problems like algorithmic bias, which could lead to reputational damage, regulatory scrutiny, or worse. Without proper oversight mechanisms, businesses risk deploying AI that may function efficiently but lacks fairness, transparency, and accountability.
As Professor Dejan Glavas points out, building responsible AI systems requires more than just good intentions. Companies need structured training programs that equip their teams with technical skills and a deep understanding of ethical risks.
“A lack of these investments both slows progress and opens the door to missteps that could set companies back by years.”
Practical guidelines and best practices could address AI challenges
When it comes to overcoming AI hurdles, what businesses need is clear direction and shared wisdom. Companies don’t need to reinvent the wheel. Instead, they need to create a playbook that balances technical expertise with strong governance. Companies need a framework that brings together three essential elements: governance, workforce development, and ethical foresight.
Businesses need systems to manage data responsibly, oversee AI decisions, and instill accountability at every step. This has to go hand-in-hand with workforce development—equipping teams with the tools, training, and know-how to make AI work effectively and responsibly.
And then there’s ethics. Companies can’t afford to ignore it or tack it on as an afterthought. Risk management strategies must be baked into the AI strategy from day one, addressing issues like bias, transparency, and long-term societal impacts. Practical guidelines and case studies could give businesses the clarity they need to chart the right course forward.
Pooling knowledge and sharing best practices, companies can turn AI from a daunting challenge into a sustainable, profitable engine for growth. It’s a win-win for innovation and responsibility. And as the AI Barometer makes clear, the time to act is now, before the gap between ambition and execution becomes unbridgeable.
