The Path to Enterprises Maximizing AI Initiative Value

Blog author Nick Magnuson's headshot

Nick Magnuson

5 min read

The process for implementing AI across an enterprise has risen from an under-resourced tech team challenge a few years ago to a board-level top priority today.

Thanks to the overnight popularity of generative AI and GPT-everything, board members are now keenly aware of the transformative potential this technology presents, whether they truly understand its nuances and complexity or not. CEOs are being asked not if they are taking action but what they are doing to take advantage of the technology and how quickly they can action it to enhance and extend business objectives.

As leadership teams scramble to form enterprise-wide positions on both strategy and execution, where exactly AI “fits” within the context of each business or how it might directly impact the objectives they oversee is not something that many clearly understand. For a number of organizations, AI is quickly becoming an integral aspect of business strategy propped up by vision, opportunity and risk management.

In order to calm the chaos of the current hysteria and set a proper course to integrate AI, below are a few recommendations for organizations looking to capitalize on the business opportunity that AI presents.

Assessing data readiness for AI

In short, there is no successful AI without good data. AI starts and ends with trusted, governed, accurate inputs. Getting to this nirvanic data state is itself a huge challenge for organizations. It is why I always recommend that enterprises first assess how ready the data they have available is for inputting into AI models. When not ready, organizations should certainly consider investing in practices and protocols to ensure data can be made AI-ready. In fact, a periodic review of data collection practices is simply good form when it comes to AI – this will guarantee that the integrity of data improves and expands over time.

Auditing for data’s AI-readiness can cover everything from where the data is located to how the data is used and what current processes are in place for collecting, storing and analyzing it. Consider who has access, at what level and how that data is managed over its full lifecycle. Once the management of data is understood, the last factors and arguably most important – data quality, privacy, security and regulatory compliance – need to be examined as well.

Identifying areas to deploy AI strategically

The disruptive nature and innovative potential of AI in business means that organizations need to be thorough and thoughtful in how they approach the technology. It has massive potential to increase revenue, reduce costs and improve productivity all while helping a business manage risk more effectively.

The identified areas that are ripe for deploying AI should take into account, and in many cases drive, the pillars of an enterprises’ business strategy. Ideally, there exists trusted, accurate data to support such use cases, as that is when maximum value can be realized. Here are additional, starter questions that business leaders need to ask and answer when identifying areas to deploy AI strategically: What is the most fruitful business opportunity we have at the moment? Do we have the resources, capabilities and infrastructure to take advantage of it and to maintain it? What competitive risk does this opportunity present? How will success be measured?

Growing staff-wide understanding of AI

Enabling employees to come along on a company’s AI journey is a great way to build evangelists and knock down barriers to its adoption. This first and foremost needs to be rooted in a culture that values growth and experimentation without repercussions for failure – focusing on the gains in human productivity that AI can bring to bear, instead of stoking fear of AI replacements.

Once plans are in place and an AI strategy is formed, it is up to business leaders to communicate the AI opportunity and build excitement for the transformative possibilities it presents. An effective approach I have seen some companies take is a cross-functional AI team. This allows those constituents to become champions of change within their own departments. There may also need to be some structural shifts but leaning on peer-to-peer collaboration often opens up an employee’s appetite for change.

Reorientating business to boost the value of AI

AI has become one of the most important growth opportunities for modern-day business. It is reshaping the enterprise of the present and the future and is affecting virtually every industry. Companies of all types and sizes need to take steps now to set their AI course, whether actual implementation is a near- or long-term goal. AI transformations don’t happen overnight and there are steps every organization can take today to ensure they have the option to maximize AI’s potential going forward.

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