What is your AI strategy?

Also, this week:

  • 🏦 McKinsey’s Global Banking Annual Review 2022

  • 🖱️ Most clicked links from the year

  • 💬 Talking Points for Life

🤔 What is your AI strategy?

Looking back at 2022, the most prominent breakthrough in my corner of the internet has been the AI generation of images and text. There is a reason why ChatGTP only used five days to reach 1 million users. It is crazy good at helping you write. But anyone that has tried to use it extensively sees the shortcomings. The best writing on this topic I’ve seen so far is this comment from Benedict Evans:

One of the ways I used to describe machine learning was that it gives you infinite interns. You don’t need an expert to listen to a customer service call and hear that the customer is angry and the agent is rude, just an intern, but you can’t get an intern to listen to a hundred million calls, and with machine learning, you can. But the other side of this is that ML gives you not infinite interns but one intern with super-human speed and memory - one intern who can listen to a billion calls and say, ‘you know, after 300m calls, I noticed a pattern you didn’t know about…’ That might be another way to look at a generative network - it’s a ten-year-old that’s read every book in the library and can repeat stuff back to you, but a little garbled and with no idea that Jonathan Swift wasn’t actually proposing, modestly, a new source of income for the poor.

What can they make, then? It depends what you can ask, and what you can explain to them and and show to them, and how explanation they need. This is really a much more general machine learning question - what are domains that are deep enough that machines can find or create things that people could never see, but narrow enough that we can tell a machine what we want?

Benedict Evans

Trying to answer the last question through Fintech-eyes, Anti Money Laundering (AML) is the most natural area in which AIs could help simplify the job. It is a field with lots of data and patterns where machines can find patterns humans would never see.

It wouldn’t surprise me if banks halved their customer service centers starting next year based on how good tools like ChatGTP are. However, this implies that the banks have structured all their previous customer interactions and data about whether the customer got what they wanted. This is an excellent example of where having a strategy for AI a few years ago would have been valuable.

National Strategy for AI

Did you know Norway has a National Strategy for Artificial Intelligence from 2020? For fun I used Open AI to summarize the 66-page document, so you don’t have to read it:

The government of Norway has outlined a strategy for developing and using artificial intelligence (AI) in the country. The strategy includes facilitating data sharing, investing in AI research and development, promoting digital skills and technology literacy in schools, and deploying a 5G network. It also emphasizes the importance of ethical principles in the development and use of AI.

Open AI

After skimming through the report, the above summary seems to be as precise as the 66 pages. In my opinion, what is missing from the strategy is what they won’t do. Now everything seems to be important, and after all, strategy is the art of sacrifice.

Deloitte has published a short primer on creating an AI Strategy. The key takeaway is quite obvious: having a company-wide strategy for implementing AI in the organization makes the organization more successful in using AI. What is worth noting, however, is that the report emphasizes the importance of aligning AI initiatives with the overall business strategy and advises against solely focusing on efficiency goals, as this may lead to missed opportunities for creating value through AI.

🏦 McKinsey’s Global Banking Annual Review 2022

McKinsey has released their Global Banking Annual Review for 2022. Quickly summarized it says that the global banking industry has faced a tumultuous year in 2022, with a combination of macroeconomic volatility, geopolitical disruption, and the lingering effects of the COVID-19 pandemic. Despite this, bank profitability reached a 14-year high.

In order to navigate the current challenges, banks will need to focus on improving efficiency, leveraging technology, and building resilience, as well as increasing engagement with clients on climate-related financing.

🖱️ Most clicked links from the year

Instead of summarizing all that happened last year, I went through all the most popular links from the newsletter over the last year and ranked them:

Based on this, there is a high probability that you as a reader, are interested in UX principles and Fintech, hates PowerPoint, and secretly find regulations fascinating. 😜

💬Talking points for life

This is the year's last issue, and we’ll come back stronger next year! To round out this year I found it fitting to share this site before Christmas vacation when everyone is spending more time with their family:

Communication is tricky. We all bring our own biases, emotions, and histories to the table. This site will help you navigate those tricky subjects, allowing you to build healthier and happier relationships. Talking Points for Life is a library of ready-to-use messages for challenging social situations.

Some examples are: