The rapid development of AI has created immense opportunity for all types of businesses, but many remain unsure on where to begin when delivering an AI strategy for lasting value. Recent research has revealed that, while around 91 per cent of business leaders are keen to embrace AI, one in three UK businesses feel they lack the skills to effectively use and implement the technology. With new advancements constantly emerging, and traditional ways of working creating resistance to change, implementing AI can feel like an almost impossible feat. When not addressed early on, however, this uncertainty can significantly delay leaders in kick-starting an AI strategy that could be transformational for their business.
Instead, leaders need to remove the fear attached to AI, generate positive conversations and drive a strategy that draws out the benefits for their business. Leaders who do this confidently, and are open to change, will be in a far stronger position to implement AI for long-term value.
The importance of experimenting
While traditional approaches to leadership have allowed for a more linear approach to change, AI has prompted an evolution of this which requires a genuine willingness to experiment. Simply outlining objectives and following fixed plans to achieve these will not suffice when it comes to AI – its constant development means that any strategy needs to be built on regular trialling, testing and reviewing in order to be successful.
Many organisations cling to the contrasting, traditional approach to change, which means getting an AI strategy off the ground can be particularly difficult. Ultimately, being prepared to experiment and make mistakes is an inevitable part of AI implementation, and possible for any organisation with the right leadership. A leader that understands the vast benefits that AI offers, accepts the vital role experimentation plays and communicates this across the board, will be in the best position for creating change that lasts.
Big-picture thinking
Leaders also need to consider how AI will progress wider business goals. While hesitancies around new technology can hold organisations back, a fear of falling behind the curve has the potential to be just as damaging. Leaders should avoid rushing to keep up with the pace of digital advancement and failing to consider how it will fit into the bigger picture – the dynamic nature of AI means that keeping business operations constantly up to date with the newest technology is simply not an achievable, or even beneficial, goal.
Instead, leaders need to implement with intention, flipping the script on traditional thought processes when introducing new systems. Rather than the typical approach of first identifying a new system or technology and then investigating how this could fit into their business, leaders should be clear on goals from the very beginning and integrate AI tools to support these. For example, some businesses may require AI for targets relating to cost reduction, while others may prioritise tools that will improve customer satisfaction. This approach will ensure new technology aligns with the strategic direction of the business, and will allow leaders to clearly communicate its value to staff.
Keeping people at the heart of change
Once leaders are comfortable with their approach, and understand the importance of experimenting with their strategy, the next step must be bringing people along on the change journey. People change is at the core of any successful transformation project and is just as crucial when it comes to AI. Just as leaders need to confront their own hesitancies, they also need to ensure this is addressed throughout all levels of the organisation.
With AI constantly advancing in the background, a typical, outdated approach to training is unlikely to have the desired effect. Traditionally, training staff on new systems has focused predominantly on the practical skills needed for day-to-day use. This type of ‘tick-box’ approach to training may be what many businesses are familiar with, but won’t be effective in isolation for a robust AI strategy. This doesn’t mean that practical training is now rendered useless, but leaders need to avoid getting caught up with excessive training sessions that focus on the ‘how-to’ aspect of new AI tools – this will become time-consuming and expensive when considering how often AI progresses, requiring further training.
Rather than aiming to make staff AI ‘experts’ through excessive practical training, leaders need to focus on building AI literacy throughout the whole organisation while addressing knowledge gaps that are often the root cause of hesitancy. By coaching people through the introduction of new tools and communicating the benefits, leaders can encourage staff to embrace a new, constant stream of change which will soon become a key part of how they work. While this won’t be easy, it’s achievable with strong conviction and the reassurance of a leader who truly recognises the value of AI.
Data is key
The value that data holds for implementing new strategies has often been undervalued, but becomes significant in the context of AI. Leaders who are data-driven, and keep this at the heart of their decision making, will be in the strongest position to drive strategy forward. Clear, accurate and organised data should be an area of priority for any business and addressing this prior to introducing an AI strategy is essential.
Data provides the buildings blocks for AI strategy, ensuring it is able to withstand the test of time and create tangible value for the organisation. Making data a key focus in processes such as measuring value, can also help to detach from traditional approaches to strategic change – some leaders, for example, may focus on financial metrics when measuring the value of their AI strategy, while others may prioritise data based on customer satisfaction levels.
The success of AI will ultimately boil down to the quality of data in an organisation, and if leaders aren’t already comfortable with making data-driven decisions, they have to understand its value and begin integrating it as part of day-to-day decision making. Clean, reliable data will pave the way for a smoother transition through an AI strategy, and leaders simply can’t take shortcuts to implementing AI without first addressing and optimising how data is used in their operations.
Setting boundaries
While leaders and staff alike should be open to embracing change, setting boundaries is also important and will help to alleviate some of the fear that can become a real obstacle in AI strategy. By establishing internal policies and communicating these across the board, leaders can help to clarify the seemingly blurred lines around AI.
These policies can specify boundaries for how AI is used day-to-day to prevent it being over-used, or abused, by staff and causing potential harm to the business. Policies should also outline ethical use along with GDPR compliance, especially as businesses start to work with increased amounts of data as they integrate AI. Addressing these from the outset, and reviewing policies as new tools are introduced, will help to prevent any legal implications of AI use becoming a barrier to progress.
Once established, leaders should communicate these policies internally to keep the entire organisation informed on how AI will be used. This will help to demonstrate that the business acknowledges some of the ‘grey areas’ of AI usage in daily operations, and takes practical steps to clarify this for staff.
Processes for continuous improvement
A successful approach to AI strategy sees leaders viewing change as an ongoing process, rather than a one-off project. To be prepared to embrace this level of change, leaders should consider setting aside a budget for the purpose of innovation and ongoing AI strategy – by financially preparing for new areas of improvement from the outset, leaders will be able to make more agile decisions throughout the change journey.
Building on this, organising an internal team or taskforce with the specific role of reviewing AI strategy can be hugely valuable. As part of this, leaders should bring in representatives from across departments, recognising the value of operating cross-functionally. For example, perspectives from representatives in finance, HR and customer service can help to build a more cohesive AI strategy and allow leaders to make informed decisions that reflect all areas of the business. It is no longer IT driven.
When reviewing the AI strategy, this team can discuss recent developments in AI and review competitors’ approaches, giving leaders the support of a varied team joined by the collective aim of optimising AI in the business. To ensure its success, leaders need to champion these conversations, being the voice of reason that cuts through the noise and makes confident decisions.
It’s clear that implementing AI requires a shift in traditional approaches to change management in order to be successful. Leaders who accept this, and are willing to embark on a journey of ongoing change, will be more prepared to face challenges, address internal knowledge gaps and identify new areas for improvement. While it can feel tricky to manoeuvre, the value of a successful AI strategy is worth the risk, and leaders who embrace this will see the benefits play out across their entire organisation.
