Upskilling staff with AI skills is no longer something that’s ‘nice to have’, rather, it’s now imperative.

Workforce and talent management will need to be top of mind for anyone who is navigating technical solutions and teams, writes Jean Van Vuuren, AVP of Hyland.

It’s crucial for businesses to focus on AI skills both within technical teams and business groups, which will require investment in technology, the right people and providing training content that introduces employees to the concept of AI.

According to Gartner, even before ChatGPT, one-third of CIOs reported their organisations had already deployed AI technologies, and 15% more believed they would do so within a year. The global research guru notes that deciding how best to proceed means factoring AI into business value, risk, talent, and investment priorities.

Business leaders have grand expectations about AI but they would be wise to acquire some level of proficiency in the technical language of AI as well as understanding the risks and opportunities for their businesses.

Without question there are bonuses attached to upskilling of both technical teams and business groups on the AI front. These include amplified development capabilities and a rapid increase in productivity. Prior to ChatGPT, most deployments of AI focused on efficiency improvement at the business unit level, rather than enterprise-wide.

Gartner says the best use cases for AI require access to enough reliable data that is relevant, logical, and high quality. AI expectations also need to be adjusted if you are to be clear on what’s feasible. Most AI business value is generated from one-off, point-to-point solutions.

Gartner emphasises getting more value from solutions at scale may require deep business process changes, and new ways of working between AI teams and software engineering.

These tools will play a supportive role in growing developers’ capabilities, hastening routine coding tasks, and highlighting potential issues. Such technological augmentations can result in boosted productivity and, on average, superior code quality.

Furthermore, generative AI tools open doors for companies to offer a new breed of software that relies not only on pre-determined logic but also on historical data and content. This enables these systems to perform advanced functions and conduct tasks not conventionally practical to do.

If used appropriately, generative AI can help eliminate old technical debt by rewriting legacy applications and automating a backlog of tasks. However, businesses should be cautioned against jumping in headfirst without the right cloud environment and strategy.

If companies prematurely implement generative AI, existing technical debt may continue to grow or, in some cases, become chronic. Organisations are rushing to implement AI without a clear understanding of what it does and how it’ll benefit their company the most.

Reduce labour gaps with AI

It’s crucial to continually find new and innovative ways to reduce labour gaps with intelligent customised AI interactions and processes, but to do so will need access to skilled teams who can build these solutions.

AI skills need to be ramped up both within technical teams, as the platforms on which teams build solutions are rapidly deploying AI capabilities, and within business groups so they, too, can understand where and how these technologies may have the most impact. The job of C-suite leaders is to ensure their businesses can train, retain and compete, for the best people capable of growing this skillset.

Generative AI is a transformational technology but the management through this transition still requires people to make it work.

We need technologies that allow seamless transitions between artificial and real interactions with an emphasis on end user control and streamlined access to data. Investments in technology and the people who can build these experiences will be the most impactful and will help drive businesses forward. AI should lead to hyper-customised and personalised interactions in the workplace and in our personal lives. People, especially younger generations, prefer these types of interactions.

That’s not to say people don’t want live customer service experiences – they just increasingly want it on their terms which is when they are ready for it. Prior to this point they are happier to work with an artificial interface to get the information they require before they will take the matter forward.

Elevating knowledge levels around generative AI, especially in non-technical business units, is no mean feat. There is excitement around these technologies, boosting momentum and justifying investment.

However, you still need to see the return on investment (ROI), which means you want to solve the right problems with the right tools. The inherent human aspect of the shift to AI is the task of helping everyone in the organisation understand what it can really do to add business value.