With the launch of ChatGPT prompting an explosion of interest in AI, businesses across all industries are now keen to jump on the trend and start driving results. In fact, 35% of companies are already using AI in their operations and 42% are looking to implement it in the future. 

This willingness from businesses to embrace AI is crucial for driving innovation in the UK however, however according to Gartner, a whopping 85% of data, analytics & AI projects fail. The issue is that many companies are jumping in feet-first and making significant investments without any strategic depth applied to their AI initiatives. Consequently, these companies are failing to attain the transformational results they set out to achieve. 

Given the current economic climate, most organisations simply can’t afford to be wasting precious time and resources this way. To ensure AI is used in the most beneficial way, it needs to be deeply integrated into a business's core through a sustainable, scalable strategy that is embraced across the organisation.  

AI applications are only worth the data they’re built on

Before even thinking about implementing AI, businesses must first assess the issues their data may create. Organisations that are too focused on how quickly they can reap AI’s rewards will likely face challenges down the line - mostly caused by poor data infrastructure, data quality, transparency and accessibility. As such, it’s important that these obstacles are addressed, and better data foundations adopted, before deploying an AI strategy. 

To do this, an organisation-wide analysis of teams can help evaluate the capabilities of different domains and product teams within a business. In tandem, a decentralised and democratised approach - such as a data mesh model - can help ensure that the data is owned and maintained by people who understand it and put into the hands of the people who need it. Finally, for a business to get the most out of AI, it must change the way it approaches data and begin looking at it as more of a product rather than a technical asset. 

The key pillars of a successful AI strategy

Once a business has established strong data foundations, it can begin crafting its AI strategy. A robust AI strategy can be broken down into five core pillars that cover the entire AI value chain across people, process and technology. The first of these is an effective AI culture, where people at all levels of a business are well-informed about its potential applications and business value. By creating a culture like this, businesses can ensure that the implementation of AI is well-thought-out, holistic and clearly aligned with business goals. 

The second pillar of a successful AI strategy is ideation. Before blowing resources on AI solutions that may be unsuccessful, organisations should first work with data experts to test if their ideas are both valuable and technologically feasible. If a business isn’t ideating effectively, it will fail to recognise major opportunities and the AI initiatives they do develop will likely be sub-optimal.

Next is delivery. Once a business has identified the most beneficial AI use cases in line with its objectives, it’s crucial to have strong AI development policies in place to ensure the end-to-end delivery process is effective. This includes setting up, training, measuring, scaling up and maintaining AI models over time. Without a proper delivery framework, a business's AI initiatives will never evolve to reach the volume and scale required to make a genuine impact. 

The fourth pillar is trust - potentially one of the biggest potential barriers to AI adoption as nearly half of all employees are still wary about trusting AI in the workplace. An organisation’s people, customers and regulators must all feel that its technology is safe, transparent and accountable. Therefore, if AI is to be widely adopted across a business, it’s vital that the solutions created are clear, ethical and abide by regulations.

Finally, the impact on a business is what matters most. AI initiatives should not be launched without being directly linked to a business goal. Success can be determined by tracking AI initiatives across a range of key metrics including performance, adoption and return on investment (ROI) to see how they have impacted business outcomes.

The bottom-line business benefits of AI

AI has become a real opportunity to achieve true business impact. For example, it can add value in ways such as improving productivity and operational efficiency, developing new product and service ideas, personalising customer experience, automating tasks and enhancing decision making. Yet, businesses are continuing to miss out on these benefits by continuing to develop AI in isolation to wider business operations. 

By investing the time to develop a deep-rooted AI strategy - centred around culture, ideation, delivery, trust and impact – AI can be cemented at the heart of a business. The companies that do this will unleash business growth and accelerate outcomes which will, in turn, help to gain a competitive advantage in today's rapidly advancing world.