Artificial Intelligence and its impact on business and jobs is a topic that has been on many business leader’s agenda. It is the topic that has witnesses the swing between two extremes: it will revolutionise how we work to it will destroy the work force and replace humans. However you look at it, extremes will never give you an objective idea of what AI can do. Up until yesterday, I had the misconception that artificial intelligence and machine learning are very interlinked.

Project Management Institute hosted its eighth event yesterday at the University of Westminster on the topic of AI and how project managers can win with it. The talk was presented by Abhijit Akrekar, Head of applied sciences and business integration at Lloyds banking group.

The talk was very insightful and triggered a good discussion amongst the project managers in the room that went from tools companies can use in AI, into the ethical use of it and GDPR regulations and data privacy.

Abhijit explained how a business can highly benefit from AI if they get it right. It is important to understand what AI can do and where its use will bring the utmost return on investment. He shared how this is not the job of data scientists alone, nor business leaders. This is joint effort that has to be the result of an organisational strategic decision and change decision. Business leaders must be able to identify and define their value proposition, process owners must ensure that data collected is clean, and data scientists must work on ensuring all data pipelines are aligned and made with no assumptions at their end when any animality arises.

An example that triggered a good debate during the event was when a company decided to use AI to determine the best suitable candidates for a key role. They fed the system all the CV’s of previous employees who were successful in the past 30 year for the machine to produce the intelligence. Sadly, due to different social context, the result was extremely biased as it automatically started eliminating female candidates. Today’s world is still not gender equal, let alone 30 years ago. The outcome of this entire expertise brought more damage than benefit. The main conclusion that I believe Abhijit was putting across is that all project managers and business leaders should not trust AI blindly. The human element will always be needed to validate the data AI is producing. After all, no machine can produce data that is socially aware and humanly astute.

The clear message is for project managers to build on their successes in the AI world, they must ensure the bridge the gap between business leaders and data scientist. Translate what data is saying interns of business language to help decision making.

Here are my key takeaways from yesterday:

  1. Bad data will always result in bad results or ‘intelligence’.
  2. Since this revolution is still not mature, only giant companies are able to afford deploying it. This is based on a shocking fact that up until now there is around USD65billion invested in the industry with over 40% of companies producing zero impact or return on investment. On the other hand, there is a 5% of companies who are able to produce over 50% of their revenue from AI.

Most importantly, I rectified my misconception about machine learning and artificial intelligence when Luca Giraudo, the chair of the London branch for PMI UK Chapter explained it in simple terms: Machine learning is based on key metrics that are defined by humans; whereas artificial intelligence is data give to machine and the learning happens without boundaries.

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