What Enterprises are Looking for in Third-Party AI Vendors

According to IDC, global revenues for the AI market will cross $554.3 billion by 2024, and AI applications will take 50% of the revenue.

Given the present market, startups that can build innovative AI solutions will end up winning big — as long as they can differentiate their services, scoop up market share and position themselves for ongoing innovation.

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Worldwide, 74% of companies have already deployed or are exploring AI solutions. One-third of global companies want to:


  • Embed AI into current AI applications and processes.
  • Use off-the-shelf AI applications or tools to build their own applications.


Mature AI adopters are also moving beyond these objectives by leveraging AI to create new products and ways of working.

Buy Over Build

A report from Deloitte states that “AI adopters tend to buy more than they build, and they see having the best AI technology as key to competitive advantage.”

But enterprise expectations from third-party AI vendors have changed.

First-generation AI applications had many teething problems; still, many enterprises gave them a chance. But now, expectations run high, and businesses want AI applications to be more accessible and easier to deploy.

Business leaders are considering three key factors before they buy any AI solutions, such as:

  • Automates processes to empower higher-value work
  • Provides trust in business outcomes
  • Ability to deploy anywhere (public or private cloud or on-premise)

As the AI market matures, startups will have to look deeper into the process of innovation and ideation to build an application that stands out and exceeds commercial expectations.

What are enterprises looking for in third-party AI solutions?


  • Reduced friction between the integration of AI solution and its use:
    they are looking for AI products that come pre-trained, are built for out-of-the-box performance and scalability and require minimal ongoing user interaction.


  • AI systems will get smarter and more accurate over time:
    enterprise AI adopters are looking beyond rule-based systems and preferring deep learning solutions that can be continually trained and re-trained — and expect AI vendors to perform real-time monitoring of accuracy metrics.


  • Easily work with data it hasn’t seen before:
    AI vendors should be able to explain how the solution works with data it hasn’t seen before or across the different verticals within the organisation.


  • Visibility and explainability of the AI algorithm:
    AI solution that can show where it pulled the data from or how it used the data to run the algorithm makes it easier for users to validate the outcome.

As the field of AI moves posthaste, businesses will need to work with AI startups to respond to the changes in the marketplace.


AI startups that can bring to market solutions that accelerate AI adoption have a vital role to play in the growth of the AI market.


Manohar Paluri, senior director of Facebook AI, says,

“One of the things that I’m most excited about is the proliferation of AI platforms so that everybody starts off not at ground zero but in a place where another researcher has ended. That is going to be one of the fundamental reasons why we will have rapid progress over the next few years.”

Register for the Imperial College Business School AI Startups & Innovation programme to take advantage of the opportunities in the current AI market and learn to articulate a business problem effectively, define a solution and conduct a competitive analysis before you go to market with your AI application.

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