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The State of AI 2017 – Inflection Point

Covering everything from technology through to implication and application – the State of AI 2017 is a must-read for any investor, early-stage founder or corporate leader looking for AI transformation.

The report does a great job of introducing AI and the implications of the technology, but also provides advice to investors on how they can identify promising early stage AI businesses.

You can read the full report here. But if you’re short on time, we’ve summarised the 128 page document with the key takeaways:

Introduction to AI:

  • Executives should familiarise themselves with machine learning, deep learning and rule-based software. They need to also identify core aspects of their company’s value proposition to which AI could be relevant.
  • Investors should have a clear understanding on the various different approaches to ML such as random forests and Bayesian networks – this will help them to differentiate companies deploying ML. Investors should be looking for businesses that are using AI to enable new possibilities.

Applications of AI:

  • Executives should look at use cases across multiple sectors to understand what can be achieved with AI. They can then look to identify business processes in their sector that could be automated, improved, or reinvented using AI.

  • Businesses should assess the extent to which they are developing the commercial success factors, organisational design and skills required for the age of AI.

  • Investors should evaluate opportunities to invest in companies built around business models that will come of age as AI disrupts old, existing markets.

Investing in AI:

  • AI acquisitions have increased dramatically, to-date averaging ten per month in 2017.

  • Investors should remain open-minded to investment opportunities in horizontal AI providers. Companies with world-class technology valuable to an AI platform provider can be an attractive technology or talent acquisition.

Richard Young

Richard has been interested in the AI space for some years. Questions of ethics can raise some serious problems. What if AI can learn who is pre-disposed to cancer and then not give them health insurance?

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