Link roundup: Artificial Intelligence

With the constant flow of articles on Artificial intelligence that are often all bark no bite, we think a good old link round-up is required to bring the most valuable resources to the fore.

Artificial Intelligence has the potential to transform business processes and deliver new strategic capabilities which will impact employees at all levels of the organization. The Covid-19 pandemic hasn’t stalled that potential with McKinsey stating in their annual survey that 56% of respondents surveyed report AI adoption in at least one function.

This all sounds good on paper, but an essential element to remember when you see statistics like the above one, is that AI adoption is not a race. While many believe AI is a “big bang” project that will eliminate our immediate tasks, among those who have really harnessed AI, they have met it with a strategic and proactive mindset that is anchored on long-term objectives. The race to leverage AI is certainly not a sprint but rather a long hilly marathon with lots of moments where you “hit the wall” along the way.

The ACTUAL State of AI

If you believe all the articles out there, your perception might be that AI is here and doing insane things for companies. The reality is more nuanced. Here is our selection of articles to help you tell apart reality from over-exaggeration.

To get a realistic picture, take everything you read about dramatic progress in AI with a healthy dose of skepticism—and rejoice in your (for now) uniquely human ability to do so.

- Gary Marcus

In fact, MLOps is a best practice that is set to have a ripple effect across a large range of industries, and the resulting efficiency is already producing unprecedented ROI for companies. The reality is that there are incredible opportunities and advantages to AI, however, implementing AI is a risk, and implementing it correctly is hard.

AI in Action - Company Case Studies
 

The idea of eliminating these lower-level routine tasks highlights some important questions on how humans will eventually work with Artificial intelligence. This brings the role of team leaders to the forefront and more specifically their ability to coordinate teams in what is known as the “new diversity” where humans and machines work side by side.

How to Manage AI within Teams
 

  • The most striking example of humans working with machines is in chess where Gary Kasparov partnered with a PC running the chess software of his choice. His learnings, along with the recommendations of David De Cremer, form the conclusion that in the end, it’s all about the process and how artificial intelligence combines with authentic intelligence (the human) to create the combination known as augmented intelligence.
  • A report on Empowering AI Leadership by the World Economic Forum fleshes out how to integrate a machine into your team dynamics. Collaboration between different departments needs to be frictionless going forward in order to scale AI within small teams and eventually expand into the whole organization.
  • After integrating this technology into teams, leaders also need to think about how to manage these AI Decision-Making Tools. Consumer demand for instant responses and real-time coordination make increased AI use within your organization an inevitability. To satisfy this demand picking the right management option for each of your AI systems will be essential.

Machines are often introduced as the new super employee and this is true to a certain extent. Their ability to eliminate repetitive tasks will be welcome news to many but this is not a “set it and forget it” system. AI is built on pillars of rigorous preparation and a clear strategy which will require commitment from every level of the organization.