Making Money from AI: Use Cases and Experimentation

G. Barton
G. Barton

Summary Bullets:

  • Enterprises should be prepared to be ‘guinea pigs’ for large tech companies seeking to develop replicable AI solutions.
  • Off-the-shelf AI solutions for vertical and horizontal use cases are being offered by a growing number of providers.

One of the biggest challenges to adopting AI is knowing where to start. In theory, AI can be applied to any and all aspects of an organization’s day-to-day operations. Furthermore, even if AI enhances a particular part of a business’s operations, it does not necessarily mean that the value returned will be worth the investment. One of the biggest beasts in the telecoms technology world, Cisco, has acknowledged that it has not brought as many AI-enhanced solutions to the market as it anticipated because it is still developing the use cases for AI.

Many businesses and organizations do, or should, have a good idea of where there biggest operational or go-to-market challenges are: for example, maintenance, stock control, or customer identification. But, knowing what the problem is and knowing how to use AI to solve it are very different things. Some of the most exciting AI test cases at the moment are only possible through the combination of research institutes, Fortune 500 levels of capital investment, and government subsidies. These projects are out of the reach of most businesses – in terms of both economic and human resources.

One of the ways that organizations can gain this funding is by volunteering to be a test case for big technology companies. If a business or public sector body can convince an AI technology provider that the challenge they face is one that exists for most similar organizations, then that technology company may well be persuaded of the value of creating a solution that can be replicated and sold multiple times over. And this is true of both the giants and startups – all of which are looking for a way to monetize their investment. Indeed, many startup acquisitions are a result of the startup having created a proven use case for AI.

Organizations should also be aware that AI providers are beginning to offer pre-packaged AI solutions for both vertical and horizontal scenarios. French telecoms provider Orange Business Services (OBS) is one such example. As part of its efforts to expand beyond its traditional telco base, OBS acquired France-based AI consultancy firm Business and Decision. However, OBS is aware that bespoke consultancy is not a way to gain mass-market share and has already developed productized AI solutions for areas such as electronic point of sale (EPOS), pharmaceutical R&D, industrial process optimization, and digital brand development and customer engagement. These bundles offer an achievable way to gain real world benefits from AI.

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