The AI sector is operating at an unprecedented pace. Every week sees a new model being launched, records being broken, and startups scrambling to create products based on the new technology.
However, there is a catch.
Too many AI companies are fighting for the same technology, the same models, and even sometimes the same ideas.
With the democratization of AI, technology alone is not becoming a source of differentiation anymore. What sets companies apart is their deep understanding of problems in order to solve them.
This is particularly evident in industrial scenarios.
There are unique difficulties encountered by manufacturers, logistics, warehousing, and infrastructure providers which cannot be overcome using generic solutions from AI systems. The equipment malfunctions, lack of visibility for the assets, errors in inventory control, safety of the workers, and operational inefficiencies affect bottom lines.
This is not just an abstract challenge but an actual business challenge that costs billions of dollars in losses annually.
Organizations making money in AI are shifting their focus towards solving operational challenges as opposed to merely demonstrating the capabilities of the AI model.
In Aperture Venture Studio (https://apertureventurestudio.com/), this approach governs the process of evaluating and developing the venture.
As opposed to using technology first and then looking for applications, one should begin with defining high impact operational issues. Once the issue is validated, then technology like artificial intelligence and Internet of Things can be used to come up with practical solutions that increase efficiency and visibility.
The sectors where these kinds of initiatives have been found to yield results are areas such as:
Asset tracking in real time
Predictive maintenance
Workforce safety
Optimized inventory
Operational intelligence
Automation of industries
The benefit that comes with working in these sectors is that results can be quantified.
In light of increasing adoption of AI, it will make companies more focused on tangible results than on technology demonstrations.
Winners of the next wave of innovations may not be companies with the biggest models.
These will be the companies that comprehend the problems of their clients better than anyone else does.
Technology moves fast. Business problems stay meaningful.
That’s why problem-first innovation is one of the surest ways to build sustainable tech companies.
More on building AI and IoT companies around meaningful business problems: https://apertureventurestudio.com/
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