Given the rapid push towards the digitalisation of business in 2020, Artificial Intelligence (AI) has gained attention and as a critical enabler in this regard. In April this year, while delivering on the company’s quarterly earnings report, Microsoft CEO Satya Nadella said that “we’ve seen two years’ worth of digital transformation in two months.” It is this sentiment of fast-paced innovation that is echoed in a recent Gartner article I came across, focused on AI megatrends.
In it, the author examines two AI megatrends that have dominated the organisational landscape this year – the Democratisation of AI and the Industrialisation of AI.
Democratisation of AI
As has been the case with other technologies, AI is no longer the exclusive domain of experts. Instead, companies are looking for ways to extend its benefits to more stakeholders in the organisation whether these are executives, salespeople, partners, assembly line workers, or developers, as the article highlights.
According to Gartner, this shift requires new enterprise roles to emerge with developers becoming a major force in the future of AI. I agree that developers and other related engineering disciplines (specifically in IT) have significant and important roles to play in creating practical AI solutions. For instance, integrating them into operational and management applications.
However, developing analytics models and AI solutions will likely always remain a specialised field.
Analytics and AI require experts who understand the techniques and approaches used to design and build the core components of these solutions. These developers and solutions engineers are vital to integrate AI into the organisational back-end by ‘translating’ the technology into practical business processes that deliver value on an ongoing basis.
Industrialisation of AI
Gartner writes that the industrialisation of AI platforms enables the reusability, scalability, and safety of AI, which accelerates its adoption and growth. This is designed to get new adopters of the technology on a similar level with early adopters to drive future value and benefits.
As part of this evolution, AI brings greater responsibility (and governance) in the establishment and refinement of processes for handling AI-related business decisions and managing AI risks. As these solutions mature, companies make fewer mistakes in designing, implementing, and using them.
I agree with this view. This is especially important to make AI accessible to smaller organisations who may not have the capacity or capability to do it on their own. As AI becomes industrialised, companies across industry sectors will be able to benefit from it. It is especially smaller companies who can grow into the management style of using AI without massive outlays of staff and technology. Cloud-based AI solutions, as an example, that are available on a usage or data volume basis will make sense for these businesses.
The past several months should be about providing key learnings to take AI and make it an indelible part of the business environment in the journey ahead.
