AI’s role in sustainable investing

May seems to have been the unofficial artificial intelligence (AI) month.  Every day seemed to bring a new development, every conversation seemed to include it, every opinion-writer weighed in on it.  The noise built to a dramatic crescendo the day before the end of the month.  On 30 May, the newly formed “Center (sic) for AI Safety” (CAIS), published the most wonderfully punchy position statement I can remember:

“Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”

Let’s park, for the moment, what climate change possibly still needs to prove before it makes that list.  Notwithstanding that oversight, the CAIS is an impressive organisation.  It’s not made up of lobbyists, politicians, or regulators: instead, these are the luminaries of the AI world itself, mostly engineers and creators who’ve devoted their lives to it.

There are plenty of other concerned voices too. And, on the other side, plenty of those that see the incredible potential, and are more sanguine about the risks.

These existential debates are now in full swing. So we should share the two key points we see right now about AI; how it impacts our strategy, and your investment.

The first, grander point is that we do lean to the more optimistic side. We kind-a have to.  Our strategy is to invest in companies that provide solutions to sustainability challenges.  In most cases, that is about technologies – tools, skills, know-how – and technical solutions. And AI is a doozy of a tool – it looks like it might be the best one yet invented.

Just how good is easy to see at ground level.  There are some incredible stories now, like Jan Oskam, a Dutch man who can walk again after ten years after being paralysed in a motorcycle crash.  AI is acting like a “thought decoder” to send the signals to his spine, that otherwise couldn’t get through.  Or, combining AI with spatial data to track and control fish stocks, apply fertiliser efficiently, reduce methane emissions, or manage pretty much anything else that moves.

The helicopter view is that AI will slice through the Gordian knots of sustainability.  We have previously talked about a VUCA world, a term we borrowed from the US military.  VUCA stands for volatile, uncertain, complex, and ambiguous.  It’s not clear if the world could ever not be volatile or uncertain.  But AI will certainly solve the complex and ambiguous.

The second way AI impacts the strategy is more prosaic.  One of the other reasons that May was unofficial AI month is that it left a pretty big print on global markets.

On 24 May Nvidia, maker of the kind of graphic-interface chips on which a lot of AI relies, issued quarterly guidance that beat analysts’ consensus by more than 50%. The stock rose 24%, taking it to over US$1trn in value, where it remains.

A host of other smaller companies which feed the AI value chain have had similarly positive experiences, both in fundamental outlook and share price. But it has boosted the “usual suspects” of the tech world too. Amazon, Alphabet, Microsoft, and Meta all have big plans for AI, and no-one (even governments) can match the money they will invest in it.

This has resulted in very “narrow” stock-market leadership. The largest ten names in the US S&P500 index have provided all of that index’s gains so far this year.

As we explained in our webinar for the second quarter of 2020, our overweight in technology stocks doesn’t include these mega-cap names. The technology they provide can be put to many purposes. We want to invest in the clever application of the core tech, to real-world sustainability challenges.

Those sustainability-focused AI companies are not here yet. Indeed they may not arrive in that form– it’s probable that those companies already experts in their fields, will more quickly learn how to adapt the tool to boost their productivity.

We are already seeing examples of this in our own portfolio. Contract research organization ICON Plc is using AI to predict the outcomes for patients in its trials. Water equipment company Xylem is using AI to predict infrastructure damage risks.  Spatialisation specialist Trimble uses AI to help minimise transportation accidents.

These are still early days though. As exciting as these initiatives are, it can still be frustrating as we watch the recent leaps forward in AI capability, and wait for it to translate into broader sustainability solutions. But we know that at the same time, the sustainability challenge is only intensifying.  As the sustainability pressure builds, the opportunity for those that can really harness this new potential will grow and grow.