Artificial intelligence is interesting, but even more interesting is the new business ideas and innovations arising from it. The catch is that the innovations have to deliver an order of magnitude greater benefits or returns than their predecessors. That’s why a startup mentality may be needed to promote any super-innovative concepts the technology could bring and move them to market quickly. But, contrary to popular belief, AI has its limits.
To date, innovation with AI has been tepid at best, says Shilpa Prasad, head of commercialization for AI and immersive ventures at LG Nova, the startup incubator for LG Electronics. Within an enterprise there are many “channels one has to navigate in order to get anything to market. The appetite for risk-taking is limited — because it disrupts a lot of existing work,” she explains in a recent interview with MIT Sloan Management Review.
Innovators across the industry agree. Deliver an AI-boosted solution “that shows improved, sustainable results in solving a problem,” urges Sam Curry, vice president and chief information security officer at Zscaler, an internet security provider. “Merely incorporating AI doesn’t make something better.” An AI-driven solution also needs to deliver “efficiency, measured in output rates across various aspects such as development, quality, sustainability, safety, and security,” he adds.
That’s why innovators and entrepreneurs “should view AI not as a standalone solution but as a strategic partner in their journey,” says Steve Thompson, chief learning officer at 5app, an integrated learning platform. “Integrating AI into the fabric of their operations enhances decision-making, refines resource allocation, and offers deeper insights into customer preferences.”
The convergence of AI and entrepreneurial makes for interesting times — and interesting new ideas. In her MIT Sloan interview, Prasad notes she is developing augmented reality approaches that will accelerate the way people learn or are trained for specific tasks. “The intersection of augmented reality and artificial intelligence will possibly change the way skilled-training transference, upskilling, reskilling, and content is going to play out,” she says. “With AI in the mix now, so much of this can be so intuitive, with a feedback loop that can be generated for both the trainee and the reviewer.”
The challenge is even the most tech-savvy startups struggle with commercializing their ideas, Prasad cautioned. “Startups are creating all these LLMs [large language models] that can be relevant to the project, but they don’t know how it’s going to actually translate. There’s still a little bit of a journey there for the startup to be able to understand it, to understand how they can use the technology that they’ve created and translate it over to a meaningful problem.”
Questions that need to be asked include whether the AI-driven product or solution is “is it demonstrably achievable based on current knowledge and will it have lasting value before commoditization?” says Curry. “While technical hurdles are acceptable, they should be solvable and comparable to previously addressed issues.”
As an AI-focused startup within LG, Prasad and her team have been developing productivity tools for the company’s 85,000-plus workers across the globe. “Everybody understands today that there is a gap in the labor that’s available in the factories from a front-line worker perspective. These are all real problems that the AI research within the enterprise is not addressing.”
Another opportunity — and at the same time challenge — is that because it is now so ubiquitous and available, AI lowers the barriers to entry for new ideas or businesses. “AI reduces the amount of effort required to create, and as that happens many more people will be able to build businesses and bring ideas that they have to market,” says Jon Reilly, Co-CEO and founder of Akkio, a generative AI platform.
At the same time, “it’s going to make it easier to start and grow a business — which means you have to be very careful about what your differentiated value prop is because it’s likely there will be more competition than ever before,” he adds.
This makes commoditization a risk. “If a solution becomes widely available with uniform quality everywhere, it ceases to be an entrepreneurial opportunity and risks becoming a wasted investment or contributing to a bubble if everyone pursues it,” Curry states.
It’s important to remember that AI is merely a tool for entrepreneurs and innovators. “It doesn’t replace them as it lacks initiative, reasoning, or sentience,” says Curry. :When AI sciences overcome these barriers, we may witness AI innovating, starting companies, and potentially transforming the way we operate.”
For now, for innovators and entrepreneurs, AI — particularly generative AI — “is a really powerful brainstorming tool,” says Reilly. “Chatting with a large language model about your ideas helps you crystallize them. It can participate almost as a partner in innovation – but it doesn’t solve for it or make the innovation happen.”
Another use case for innovation is that AI “allows more test and learn opportunities in different iterations of products and services,” says Casey Terrell, advisory board member of Rad AI. These now have to be done manually and are fallible due to human bias and expectations.
AI may even help systemize the innovation process, long seen as an “informal or one-off by blending serendipity with data-driven insights,” Thompson says. “Analyzing extensive datasets allows AI to uncover patterns and correlations that may well elude human observation.
Machines can do a lot but can’t replace the human ingenuity that builds businesses. “Be mindful of is the inherent difference between AI and human creativity,” says Terrell. “While AI excels at processing data and identifying patterns, it may lack the nuanced creativity and intuition that human brainpower brings to the innovation process. Relying too heavily on AI could limit our exploration of unconventional or out-of-the-box ideas that human minds can generate.”
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