AI is big business and a major focus of R&D and acquisitions – especially for tech giants such as Facebook, Microsoft and Apple. AI also garners significant media coverage, whether it is for driverless car technology, worries about AI-enhanced cyber criminality, of for AI’s potential benefits to humanity – such as using AI to help the homeless. But many of these use cases are future looking or speculative and don’t necessarily offer great value to those investing in AI – either as a provider or an end user. So how will businesses and public sector organisations make money from AI in their everyday business?
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 organisation’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.
How to make money from AI: the cost of development
Many businesses and organisations 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.
Be prepared to be a guinea pig
One of the ways that organisations can gain this funding, and so make money from AI, 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 organisations, 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 monetise their investment. Indeed, many startup acquisitions are a result of the startup having created a proven use case for AI.
Organisations 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 the 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 productised 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 achieve real world benefits from AI.
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