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3 Factors That Lead to An AI-Based Product’s Commercial Success

3 Factors That Lead to An AI-Based Product’s Commercial Success

Abhishek Sharma
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When it comes to commercial success in the longer run, not every tech pulls off the same way from others. There are many reasons for this. Here we highlight three key instances why a technology may or may not make it big in the market.

How Will The New Tech Solve Current Problems Better?

Data science, machine learning, artificial intelligence — all of these fields have emerged to be the trendsetters now. Almost every business entity wants to tap into this trio to optimise their products or services. But, the core focus should always be the business problem it solves. The “build a better mousetrap” metaphor holds good only if new technologies like these supersede existing methods or practices. A typical example would be chatbots for banking. In our earlier article, we saw how Indian banks are deploying chatbots to resolve customer queries. Here, the agenda was not only resolving queries efficiently but it also to improve customer service by leveraging tech.

As you can see, the context of customer service is the highlight here. By improving through tech, it can bring it a totally unique experience in problem-solving.



Inferring from the above example, any business has to look for innovations that make an impact rather than simply implementing them. Companies cannot afford to shell out big money to become tech-savvy.

Will The New Tech Turn Into An Oddity?

Leaning on the first point, another important aspect to be kept in mind is to not be strange to use. New tech must be looked into why it should be there in the first place. Let’s consider the example given by Rodney Brooks, a robotics expert and founder of Rethink Robotics. He explains how the concept of ‘flying cars’ is fraught with difficulties to come into a fruitful existence.

“The problem is hard because a flying car combines two completely different engineering regimes. It’s not straightforward to engineer something that can both fly thousands of meters above the ground and also fit within the narrow space constraints that a road and highway network imposes on conventional automobiles, all the while meeting the diverse safety and efficiency requirements of flight and ground transport. Optimising for one regime means scanting the other.”

How can this be strange? Flying cars are good, right? Not really. This dreamy tech cannot be commercially feasible for people even if it successfully tested, brought into the market and solves the problem of transport. On top of this, it comes with side-effects, which means, anyone owning a flying car may become anti-social.

Where ‘flying cars’ actually fail compared to regular transportation is that the latter has already fulfilled the needs and does not require any major changes. Just like this, two more examples are virtual nursing and robot journalists. Both of these are intuitive and attractive to implement in their respective areas but ultimately the essence is the question of relevance for problem-solving.


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Remember The Take-Off Period

When an idea of a new product/service/technology is born and brought into action, not all of them become an instant success technically or commercially. Facebook is a good example of this. Although it was launched in 2004, it took a couple of years to pick up globally. Eventually, websites like Facebook and Twitter led to what is popularly now known as ‘social media analytics’. In fact, this social media boom slowly made into the marketing domain and became vital in most of the tech companies’ decision making.

As evident above, Facebook had to wait for a certain period to officially ‘make money’ from its advertising strategy. Similarly for any tech to gain a solid footing commercially, sometimes it is inevitable that it has to wait for a few years (or probably more). Leaning on this, another example is autonomous driving. This area of tech has seen a lot of ups and downs in the past decade. Even though there is aggressive pushing in terms of deploying autonomous cars on roads by various automobile and tech companies, it still has to bear the test of time to become a full-fledged next big thing.

One more classic example is cryptocurrency. After its inception, it was rarely in news but after 2013, it gained traction. In fact, the boom was so high that they fluctuated in thousands of dollars in value within a short period. It also saw the blockchain technology take off in BFSI and healthcare sectors, among others.  

Conclusion

These instances are a food for thought if upcoming technologies are here to make a mark in terms of profit-making. Ultimately, new tech has to be built more around its practicality, else it is bound to vanish without a trace in the tech market.

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