The world of AI innovation can feel like a bustling airport in the height of summer – full of brands and ideas taxiing to the runway, engines ready. Yet, for many businesses, the fear of what could go wrong keeps them grounded. They recognise AI as a cornerstone of the future, but hesitation over data security, compliance and ROI prevents meaningful takeoff.
Watching from the sidelines
The fear of AI is not unreasonable, and there are very real reasons for enterprise leaders to feel apprehensive. In Workato’s survey of UK business decision makers, governance, closely followed by privacy risks, were identified as the biggest barriers toward implementing AI tools – and it’s no surprise. Widely reported issues such as data privacy and confidentiality of sensitive information, potential bias and inaccuracies, and failed ROI are enough to severely damage the reputation of an organisation and create major financial blows, as we’ve seen from the countless headlines focusing on all the times that AI has gone wrong. Remember when McDonald’s called time on three years of AI efforts after customers took to social media to complain that AI could not understand simple drive-thru orders? Or when Air Canada had to pay damages to a passenger after its virtual assistant gave them incorrect information about bereavement fares?
Safety and regulation when implementing AI, especially when global regulation is not yet established or consistent, can often be viewed as a hurdle that would be easier to avoid. More ambitious and ultra security-conscious enterprises might consider building their Large Language Models (LLMs) to take more control over privacy and data security. For some, this option gives the best of both worlds – the ability to control their own data and have an inside-out view of the technology they are using. However, this option is not a quick fix and requires a substantial amount of time as well as specialist expertise, money, and compliance hoop-jumping.
The price of waiting for the “perfect” strategy
But the antidote to AI paralysis is not to wait for a flawless solution – in fact, many businesses are already being left behind.
With so much uncertainty and risk, many organisations are simply watching innovations progress while preparing to either run away from or push back against any significant AI and automation investments. But this AI paralysis isn’t just costing time; it’s costing market share and innovation. 87% of workers say AI automation saves them time; time that can be well spent ideating and driving the business forward, and 70% of workers observe positive changes in collaboration and innovation since adopting AI. In an increasingly competitive and commoditised world, time for innovation is critical to winning customers. Sitting back and doing nothing to address the fears and uncertainty is not protecting the business; it’s putting them behind.
Facing the fear of AI
It’s age-old advice that to fight your fears, you need to face them. The more that leaders learn and share their AI knowledge amongst their colleagues, the less scary it seems. Gaining a better understanding of how bias emerges in LLMs and how it can be avoided, as well as security and any legislation that a business might fall under, puts the whole organisation in a much stronger position to innovate with AI.
Just as the captain and cabin crew on a flight are trained on safety, regulation and the workings of the aircraft, understanding how AI works and the impact it can have on an organisation is essential for the entire organisation, not just those at the top making the decisions. One-third of people say that they are not taught how to implement automation, despite their company being bullish on AI. Literacy in AI is critical to make informed decisions. It’s down to the IT leaders to prioritise training and education, so that employees feel empowered to experiment and learn about AI in a safe and responsible way that goes beyond a few training sessions. Consider regular AI literacy sessions, dedicated experimentation environments, and leadership enablement programmes that give teams confidence to innovate responsibly.
But knowledge alone isn’t enough. Often, when businesses treat AI as a “quick-win” solution to fragmented issues, the results are less impactful and much harder to show ROI. Organisations need to back that understanding with a holistic AI strategy that connects learning to action and experimentation to measurable impact. A Microsoft study found that more than half of business leaders admit their organisation lacks a formal AI strategy which is the biggest obstacle between ideas and putting them into action. By having a more strategic, enterprise-wide approach, AI can be truly embedded within the organisation in a way that will help to build towards long term goals, manage risk and build confidence amongst employees.
Focusing on the journey not the take off
Progress doesn’t come from waiting for the perfect flight plan. It comes from learning the instruments, trusting the process and taking off. Even when conditions aren’t clear. The businesses that embrace responsible experimentation today will be the ones charting the flight paths of tomorrow. The destination is worth it.
