Gartner’s 2020 AI hype cycle has a lot of encouraging things to say about the state of the tech. Some of the key takeaways include:
- Investment in AI has remained steady in 2020, even accelerating in one-third of cases
- AI leadership is coming from the very top with CEOs often taking ownership of new projects
- There may be ‘Sci-Fi’ applications around the corner… but Gartner recommends focusing on the here and now
#1 AI investment has weathered Covid disruption
Should businesses limit AI investments during the ongoing period of uncertainty around Covid 19? The answer seems to be ‘no’. Gartner’s research finds that almost half of businesses are leaving their investment unchanged. A further 30% are actually increasing their investment.
This tallies with the experiences of many vendors who were able to wildly exceed their advertised business benefits. While contact volumes increased and traditional contact channels reduced capacity, businesses were able to call upon an almost inexhaustible reserve of automated service options.
#2 AI is in a process of democratization
AI is moving away from being the exclusive preserve of experts. This is a necessary step in the widespread deployment of AI technology as a greater pool of talent will be needed to deploy and manage new systems.
Gartner sees developers as a major force in AI. As the barriers to entry get lower, there’s also space for professionals in CX design as well as data scientists, executives and IT professionals.
The proliferation of low-code and No-Code systems is very likely to accelerate this democratization. What remains to be seen is how enterprises will form AI-focused teams and assign responsibility for new initiatives.
#3 New initiatives have high-level endorsement from C-Suite
Gartner’s research shows that 30% of current AI projects are owned by CEOs. This is a promising improvement over previous years when responsibility for AI has often resided with relatively junior executives.
This high-level endorsement indicates just how many businesses anticipate substantial returns on AI investments. CEO involvement is a clear indication that AI projects are taking priority.
This level of commitment has likely been vital during 2020 and goes some way to explaining the steady level of investment.
#4 Customer service will remain one of the key applications
Gartner has repeatedly revised its prediction for chatbots implementations upwards. The most recent research Gartner projects a 100% increase in adoption over the next 2 to 5 years.
The same is broadly true of several other customer service applications for AI. Customer service is generally the use case with the greatest ease of deployment, fastest ROI and clearest objectives.
Nonetheless, plenty of businesses have been forced to revise their timescales for deploying self-service automation due to Covid. Implementations which have languished on ‘to-do’ lists have taken on new importance as contact volumes increased.
#5 Some use AI use cases are finding homes on other hype cycles
Several AI deployments have left the AI hype cycle this year. Conversational user interfaces, speech recognition and virtual assistants have all moved to the natural language hype cycle; other technologies have similarly found homes in more narrowly defined environments.
This fairly substantial change is indicative of the growth in AI technology and the large niches that it’s creating. Of course, AI is already a general topic; if new technology routinely finds more specific niches, it’s likely that the AI hype cycle will remain a home for immature technology.
#6 Gartner recommends a focus on narrow use cases over AGI
Artificial General Intelligence (AGI) is the hoped-for golden goose of AI. The potential applications of AGI are too numerous to list and would represent a paradigm shift for any business that could access it.
However, AGi remains purely hypothetical; at this point, holding out for AGI is like forgoing driverless car technology in the hope that teleportation will be invented. Gartner’s recommendation is that businesses focus on the many specific use cases AI offers.
#7 The AI hype cycle is still relatively immature
There are a number of AI use cases which already demonstrate significant value. Nonetheless, most technologies listed are still in an early stage of the AI hype cycle.
This group of technologies has a notable capacity to capture the imagination, which may be why so many linger at the ‘expectation’ stage. It’s also possible that the fragmentation of the list (as maturing technologies move into separate and more specific hype cycles) is to blame.
An interesting comparison is the hype cycle for supply chain logistics. The technologies represented there are distributed far more evenly, with more resources already achieving productivity.
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