Two megatrends – industrialization of AI platforms and democratization of AI – indicate that production workloads and high-scale AI applications are looming in the near future. We recently published for the wide audience 2 Megatrends Dominate the Gartner Hype Cycle for Artificial Intelligence, 2020. I wrote about industrialization of AI in my previous blog post. Now, let’s talk about democratization of AI.
Early adopters were like bicyclists: Data scientists put a lot of effort developing solutions from scratch to get to the destination – delivering value to their companies. Like bicycling, AI was exciting and took early adopters to the unknown places. This is the time of the enterprise in AI. Many enterprises are already running AI solutions and appreciate their fruits, but now, they want to get to the next level of AI benefits by delivering AI value at scale. The enterprise’s goals are to move fast, via known routes and serve a lot of people. Such a shift is what causes the megatrends of industrialization of AI and democratization of AI. Enterprises need a bus – a modern, industrialized AI platform. Production deployments require scale, predictability and automation.The bus – an industrialized AI platform – is a public transportation. It can take many more people and with more comfort. Its driver has a license and passengers have tickets.The bus goes on schedule and has designated stops, but the bike can go where the bus cannot. So, the best approach is a combination of data scientists who venture into the unknown and others who enjoy the fruits of democratized AI.
Democratization of AI on the Hype Cycle for Artificial Intelligence
In the enterprise environment, the target for democratization may include customers (even Things as Customers), business partners, corporate executives, salespeople, assembly line workers, professional application developers and IT operations professionals. The best approach to AI prominently represented by the Augmented Intelligence profile on the Hype Cycle for Artificial Intelligence, 2020 is when AI helps people do their jobs and live their lives.
The democratization of AI involves new enterprise roles required for delivering AI to the wide audience. It’s a job of AI teams to deliver a stable solution quickly. Therefore, not just data scientists and data engineers, but also developers participate in putting together AI solutions. Gartner foresees that developers will be the most massive force in AI – this is represented on the Hype Cycle by the AI Developer and Teaching Kits profile, still on the Trigger. In fact, when we speak about AI at scale, engineering is necessary to complement science. Data science deals with discovery of the unknown, but engineering provides stability, reliability and security of what science delivers.
Democratization of AI brings forward Digital Ethics that remains at the Peak. AI must meet very different people and cultures in a friendly and ethical way, non as a killer robot or an aloof offender – it requires the systems of values and moral principles. The bus driver, leadership of the industrialized platforms, has a license – this is reflected in AI Governance. The passengers have tickets – Responsible AI is necessary for that.
AI will be reaching significantly more people via democratization of AI, and it requires industrialized platforms that accelerate and automate the AI development and implementations process to make AI accessible to the masses. The democratization of AI means that AI is no longer the exclusive preserve of subject matter experts. Instead, it is increasingly within the reach of users in various roles, of different skill levels, and especially of diverse levels of creativity and insight. All aboard!
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