AI promises to make businesses of all shapes and sizes more efficient, more innovative, and better prepared to deliver whatever their customers want.
However, it will also inevitably expose them to new dangers and risks.
In fact, the risks of implementing new technology often scale in line with the potential for positive transformation – and with AI, that potential is huge.
So here are some of the biggest mistakes that I believe businesses will make this year as they race to implement it:
1. Failing To Align AI Strategy With Business Strategy
One of the mistakes I see many businesses making is rushing to adopt AI simply because they’ve been told they should do so without understanding how it fits with their overall goals.
This approach – putting technology before business strategy – is probably the number one driver of failed AI initiatives and – worse still – disillusionment and giving up on AI altogether.
It’s easy for us to get so excited by the hype around AI that we rush out and start spending money on tools, platforms and projects without aligning them with strategic goals and priorities. This inevitably leads to fragmented initiatives that fail to deliver meaningful results or ROI. To avoid this, always “start with strategy” – implementing a strategic plan that clearly shows how any project or initiative will progress your organization towards improving the metrics and hitting the targets that will define your success.
2. Underestimating The Impact Of AI On The Workforce
Implementing AI is likely to mean big and possibly frightening changes for the people who make your business tick.
While it won’t mean they all become redundant, it may mean they need to learn new skills or adapt to new ways of working. Assessing the skills and possibilities of training or reskilling, ensuring there is buy-in across the board, and addressing concerns people might have about job security are all critical.
Many businesses will make the mistake of thinking solely about the technical steps they have to take while forgetting that humans will still ultimately be responsible for success or failure – and this is a serious error.
3. Giving Up Too Quickly – Or Too Slowly
Not every AI project is going to work – in fact, recent Gartner research puts the current failure rate of AI initiatives at around 85%. But getting it wrong the first (or second, or third) time isn’t necessarily a reason to give up. I firmly believe that just about any business can benefit from AI, but that isn’t the same as believing that they will benefit right away or that all they have to do is launch an AI project and they’ll immediately be successful.
On the other hand, being slow to pull the plug on projects that aren’t working out can also be a recipe for disaster – potentially turning what should simply be a short, sharp lesson into a long-term waste of time and resources. There’s a reason that “fail fast” has become a mantra in tech circles. Projects should be designed so that their effectiveness can be quickly assessed, and if they aren’t working out, chalk it up to experience and move on to the next one.
4. Failing To Properly Assess The Cost
Like the previous trap, this one is also two-pronged – it can be easy to both overestimate and underestimate the cost of developing AI initiatives, and both can be problematic.
Make no mistake, going full-throttle on AI is expensive – hardware, software, specialist consulting expertise, compute resources, reskilling and upskilling a workforce and scaling projects from pilot to production – none of this comes cheap. The question of how much it costs to get an enterprise AI initiative off the ground is similar to “How long is a piece of string?” but most estimates go into the millions.
At the same time, lots of smaller businesses will be put off because they think AI is only for big companies with huge IT budgets, ignoring the fact that there are ways to implement AI cost-effectively while still providing real benefits.
Again, the answer is thorough preparation and being as accurate and diligent as possible in your costing before jumping headfirst into AI.
5. Letting The Competition Pip You To The Post
Of course, despite all of the precautions covered here, perhaps the biggest single mistake would be deciding it’s too difficult, risky and expensive and choosing to sit out the AI revolution entirely.
Make no mistake: AI is set to transform every industry, and those who do stick their heads in the sand and pretend it isn’t happening are going to be left behind.
AI will make businesses more efficient, meaning those that don’t implement it at all are effectively throwing away money. But it will also drive innovation, meaning competitors that do adopt it will create new products and services, redefining customer expectations and leaving laggards looking decidedly old-hat.
Don’t Fall Into These Traps
I know from my experience of working with companies of all shapes and sizes on digital innovation strategies that these hazards and pitfalls will cause many businesses to experience big problems in 2025.
Understanding the risks and having the foresight to see them before falling into them headfirst is the key to success, as well as the secret to delivering AI-driven growth and transformation.
By aligning AI projects with business goals, ensuring your people are included in everything you do, accurately assessing costs, and knowing when to press ahead and when to quit, you give yourself the best chance of avoiding making these mistakes.
This will result in AI projects that deliver better returns and, perhaps more importantly, prepare your organization for the even bigger opportunities that are yet to come.