What does HR need to know about Artificial Intelligence and Machine Learning?

I was so honoured to have a chat with the entire Singtel HR team at the SOTA Auditorium (yes, the HR team is "that" big) about the implications of Artificial Intelligence and Machine Learning on HR, and observations from the last 9 months of working with data-driven enterprise change programs.

Some key themes....

1. As you work with leadership on messaging, stop using "negative" words like "disruption". Scary, threatening words will simply unsettle the already-spooked employee base.?Instead, focus on the fact that this transformation will allow us to do the work that we really want to (fun, innovative, and value added). Don't shy away from the fact that people will need to adapt to new working models and learn new skills, but at the same time, don't set yourself up for an emotionally-charged change resistance. Don't be a "glass half-empty" leader when you communicate.

2. Remember Amara's Law and breathe, but make that a deep breath. As humans, we tend to overestimate the impact of technology in the short-term, and underestimate the effect in the long term.?As we see in the last 5 years of Garter Hype Cycles on AI/ML, while enterprises need to act with urgency and intent, there is no call for headless-chicken behaviour.?We have a solid 2-5 years to get our technical and non-technical infrastructures in place to support data-driven businesses before it is “too late”. With that said, if you are starting now, appreciate that you have already missed the first-mover moment. But you can still hold pace as a fast follower if you make this a priority now. With that said, the digital divide is logarithmic. So, the competitive advantage gap between data haves and data have-nots will quickly widen from here. In other words, if you continue to have a wait-and-see or put-a-toe-in strategy, I won’t be so positive in 18 months.

3. Don’t force IT to drive enterprise data strategy (alone).?AI/ML will be used to generate value for customers and employees more than any other groups, so Sales, Product Owners and HR must take an aggressive role in setting the agenda, defining constraints, goals, and priorities, and experimenting. Leaving this to the Platform team will result in an unusable platform, mis-configured for the needs of the users in the long-term. I guarantee that they will welcome you to all the meetings with open arms, but you need to roll up your sleeves and commit to the collaboration. Once the fundamentals of data strategy are designed into the platform choices, you won’t be able to easily go back later and revise – and IT already started this work…like…yesterday. So if you are not an active part of this team today, you are actually already late.

4. Use the Cloud, please.?Don’t try to build, own, and enhance your own data platform. The ability to enjoy cost efficiencies, the need for speed, the need to be able to scale up and down immediately and unexpectedly, the need to leverage industry standard security and regulatory demands all mean that you should get out of the IT platform business and focus on how you use the platform to drive competitive value.

5. Don’t forget the non-technical aspects of Digital Transformation. After all the years of using a Horse and Buggy, you have finally bought a Ferrari (Digital Platform)!?Then, what do you do? You hook up the old horses to the front bumper of the Ferrari and start dragging the car along. STOP.?Transform the horses of Culture, Leadership, Innovation, Governance and Controls, and Operations.?Run the platform to its full advantage. Transform your business, not just the platform! If your business is not setup to run in an Agile way, then all the Agility benefits that come with the Cloud for free will simply wither from disuse.

6. You can start small if you are nervous, but get going now and focus on the “right” opportunities. Identify some lower-risk use cases around “Ideate, Co-Create, Learn, and Decide” and start building controls to address “amplification of existing biases, dangers of human gullibility, and new privacy, security, and regulatory challenges” (you had to be there to get the details of these categories. Buy me lunch and I’ll share)

7. Encourage and celebrate collaboration with AI/ML tools.?Make an extra effort over the new few years to show your teams that it is safe for them to try things out. Aggressively communicate permission, even if they were not actually asking. And celebrate data wins whenever you can.?A personal example – my son at ACS was given a class assignment this week to use ChatGPT to compose a persuasive presentation on climate change and then write an essay to critique and extend that presentation.?I love that Singapore schools are embracing rather than blocking. As leaders, we need to do the same and stay on the front foot.

8. Stop thinking about ChatGPT as your future.?Generative pre-trained Transformers trained by experts overseas and pointed at the Internet will be part of your toolkit, but the real competitive advantage will come when you point [YourCompanyName]GPT at your proprietary data sources, typically, product, customer, or employee data, and train the models with your own data and data experts.

If you are finding that your digital transformation programs are stalling, lack direction and vision, or are too technically oriented to drive business value quickly enough, let's have a chat!

Bill Randall Navin Wathan Seiyi Goh #digitaltransformation #cloudcomputing #aiml #genai #humanresources