Understanding the different applications of AI, identifying clear use cases and setting realistic timelines are crucial elements of a successful AI strategy, says Yohan Lobo, Senior Industry Solutions Manager, M-Files.
Up until recently, a problem faced by technical teams across industries has been winning the backing of the C-suite for AI projects, with executives often put off by high initial costs without a clear roadmap to ROI.
However, AI has quickly become a status symbol that signifies a firm’s technical sophistication. Management teams are now desperate to integrate AI solutions to prove they are ahead of the times and, crucially, ahead of competitors.
Recent research by Cisco revealed that 97% of CEOs are planning AI integration – but fewer than 2% feel fully prepared.
This raises a big question: are business leaders pursuing AI for AI’s sake, without fully considering how this technology can best drive positive change within their organisation?
Artificial intelligence is more than just GenAI
GenAI has captured the imaginations of businesses on a global scale, but there are a myriad of AI tools we’ve been using for years that have received nowhere near the same level of acclaim.
The primary benefit of AI is to automate processes and reduce the burden of administrative work, with traditional AI focused on performing singular tasks with optimal efficiency. For example, this technology can automate permissions on files, ensuring any information end-users are not allowed to see remains undisclosed.
While AI is the umbrella term, GenAI more specifically is able to function beyond a defined subset of rules, processing inputs to formulate original content. A common use case of GenAI is natural language assistants, which support users with finding information, summarising documents, and even performing translations.
Recognising the importance of GenAI solutions, without becoming consumed by this technology, is an important element of the AI roadmap. AI tools that enable automation and boost efficiency – without the bells and whistles of GenAI innovations – can be just as valuable, so it’s important to present the full spectrum of AI’s capabilities to the C-suite.
Use cases are key
Management teams typically have a broad interest in the general concept of AI integration, with their vision less concerned with the specifics of an implementation strategy. Therefore, it’s frequently the teams tasked with AI’s deployment who are responsible for conceptualising the overarching goals of a project.
A tried and tested starting point is to ask the question: what can this technology actually do to improve the performance of the business? The answer centres on identifying tangible use cases that will become the bedrock of successful integration.
To ensure that the implementation phase is focused on activity that will add genuine value, an effective approach is to begin by fully understanding the challenges or opportunities the firm wants to address. This means looking for the problems or objectives first then developing the tech to meet these targets, rather than the other way around.
A tool with no tangible value can become an obstacle for future transformation using the same technology, so establishing a clear purpose for all AI endeavours is the only way to earn approval from both management teams and employees.
Where companies will encounter difficulties is if they try to run before they walk. Starting small and prioritising the low hanging fruit − before transitioning to more complex issues − increases confidence, generates good news stories and builds momentum. A steady stream of positive insight will keep senior leaders onboard, increasing the chances they will give their backing to future projects.
Set realistic timelines
To deliver an effective AI strategy, firms should draw together a detailed roadmap that clearly outlines the end goal of the project, how this will be achieved, and how long this will take.
Whether a team is collaborating with external partners or developing an AI tool from scratch, these processes take time and there will inevitably be initial problems in getting AI solutions up and running. This is why it’s essential to communicate with the C-suite and help them understand AI implementation is a long-term process.
The practical exercise of integration is often a case of trial and error, so it’s important not to panic if tools don’t perform exactly as intended from the outset. This may involve working with vendors and seeing how they can tailor solutions to suit the requirements of the business or performing extensive testing on internal tools so that they are only rolled out once they are absolutely ready.
When the time comes to introduce solutions to the wider workforce, company-wide training on how these offerings can be used to improve efficiency is essential. AI will remain unused if employees cannot conceptualise how this technology will increase the speed and accuracy with which they work, so taking time to communicate the potential uses is a worthwhile investment.
Achieving success in an evolving business landscape
The narrative has flipped on its head: AI is now a must-have in the eyes of leadership teams, not simply an added bonus. Enthusiasm must be coupled with pragmatism to ensure success, with a firm objective at the end of a project always the priority.
Ultimately, the overarching direction must come from development teams themselves. Ensuring that the C-suite is kept up to date with plans for the AI journey is the only way they will understand the balancing act at play, with tangible use cases the simplest way to convey the benefits.
