Worrying about implementing AI effectively in 2024? Here are my 3 top tips 

Ian Ray, Head of Data, AI and ML, Daemon discusses his top three tips for successful AI adoption in 2024 
Ian Ray

Businesses are exploring all avenues to level up all facets of their operations. AI has proven to be a clear favourite. Our recent research into businesses' attitudes towards digital transformation found that 99% of organisations are looking to use AI or ML to seize new opportunities. Appetite is particularly strong in the retail, distribution and transport sector, where 97% of organisations report either ‘some’ or ‘significant’ adoption of AI. Further to this, 98% of organisations have some vision for the use of AI and the majority are planning to implement it within the next six months. 

Despite these encouraging statistics on AI adoption, 49% of senior decision makers have low confidence in its implementation. So, while there may be a vision, it’s apparent this doesn’t align with the technology and change management deemed possible right now.  

So, how can leaders overcome this? Here are my top three things to consider before implementing AI to ensure it will have the greatest return on investment (ROI) for your business.  

Identify your specific need  

AI’s dominance in the media has made it tricky for leaders to decipher what is relevant, or even where to start with adoption. After all, if your competitors are implementing the technology, doesn’t that mean you should be too? While AI tools and solutions are much more accessible, that doesn’t mean you should rush to implement them. I advise working with the rest of your company stakeholders to identify the need for AI and assess what challenges you may be trying to address.  

For example, retail has shown a clear appetite for AI and ML adoption and is already using this to support with fraud detection (54%) and personalisation (40%). However, there is also intent from these organisations to implement this tech in the next 6-12 months to support with chatbots (23%), forecasting (19%) and automation (10%).  

This decision should also not be made in siloes. As implementation can affect all elements of your organisation, everyone should be on board and understand the reason behind eventual usage.  

Once you know you’re why, you can start building your roadmap to AI adoption.  

Alleviate any concerns 

Ahead of implementation, it’s important that you address any concerns about the technology. 49% of decision-makers said they have concerns about data security and privacy around AI, which emerged as the top driver of low confidence among organisations. Other cited concerns including legacy technology holding organisations back (29%) and a perceived low skill level within the business (24%). 

These concerns could be limiting your organisation's potential. To navigate this effectively, leaders should clearly communicate the benefits to the business and educate stakeholders on specific use cases, potential ROI, and how AI can enhance operations. Knowing the tangible benefits will build enthusiasm and advocacy for the new solution throughout the team. . Investment should also be made in training on AI best practices. To implement AI responsibly and effectively, staff need skills in data preparation, model validation, ethics, and more. Training, and the knowledge gained through greater understanding will boost competence and ease concerns. 

Organisations can also perform controlled testing ahead of a wider roll-out. Some organisations can suffer from ‘unknown unknowns’. Continued questioning of the what-ifs could slow down your road to implementation. By piloting AI projects in low-risk environments to demonstrate capabilities, companies can quickly build trust. Small-scale testing can uncover challenges early and pave the way for wider deployment. Failing fast and often helps build a more robust and successful solution without the burden of long timescales, resulting in value being released early, and mitigating the risk of a disparity of the planned ROI.

Enlist support from experts 

It’s clear that while organisations can see the potential of AI and ML, they currently do not fully understand what it can do for their organisation. Our research also uncovered that 97% of organisations agree that when they undertake transformation programmes, they could have a better understanding of what it is they need to solve. 

Over the past two years, more organisations (43%) have called for strategic support with the issues they are trying to resolve – up from 19% in 2021. Pressure from customers is cited as the most common trigger for hiring a digital transformation consultancy, increasing by 17% points over the past two years. 

Undertaking digital transformation efforts is no small task when businesses are being squeezed by turbulent economic pressure, smaller budgets, changing consumer needs, and the rapid evolution in the application of new technologies such as AI. In this context, organisations will not achieve their goals with a one-time “digital transformation”.  Enlisting external expertise can help you to build out your AI framework for implementation which will drive the most success. While there is a requirement for organisations to set out a strategic route to maximise business impact from their digital initiatives, you may need to adjust that route and the associated digital investment priorities over time, considering business strategic direction, external trends and insights, and the customers’ perspective. 

AI has surpassed being a non-tangible technology that will come to fruition in a few years. AI is here now, and organisations are quickly adopting and reaping the benefits to internal operations and customers. While strong economic headwinds have resulted in organisations accelerating their spending on digital transformation, AI has forced organisations to reimagine a digital future beyond the confines of the current ways of working. 

However, while it is tempting to sign up to the newest technologies, only invest in those that will have true business impact. The real winners of the AI race will have a well thought out strategic plan for implementation.  

Written by
Ian Ray
Written by
January 30, 2024