How You Can Become the Go-To AI Expert and Help Your Company Thrive

Good morning. What a week. I don’t share much about my day-to-day work at Rivian here, but I must make an exception this week.

What happened?

We announced that we (Rivian) are entering into a joint venture with Volkswagen + landed an up to $5 billion investment from them.

The joint venture with one of the world’s largest automotive companies is a testament to what our amazing teams have built. Our software and zonal compute architecture will be a foundation for future development in our aligned partnership.

Automakers have scrambled for years to bring this architecture to life without success. We did it, and it dramatically reduced complexity and cost. We will bring it to a massive scale through the Volkswagen Group. It’s wild if you think about that we launched our first cars less than two years ago.

Fun fact: I grew up 20 minutes away from a large Volkswagen plant in Germany. Many of my friends found their careers with VW while I moved to a different continent. Somehow, they found a way to reel me in again, and I end up so close to “home” again. I am excited about what lies ahead.

Now, back to our regularly scheduled program.

Today, we’ll look at some data about AI’s impact on work, paths to more adoptions, and how YOU can get a massive career opportunity from doing just a little bit extra work and reap huge rewards by helping your business evolve in the age of AI.

We can read everywhere that AI is taking jobs away. But the opposite is also true. New roles evolve quickly, setting us up for exciting career paths.

Today, I want to discuss an evolving new job function and why companies should consider introducing it to their organizational structure.

I will also discuss how YOU can, if you desire, pave your path into this role.

5-minute-read

AI has staying power

What happened when Italy banned AI:

• When Italy banned ChatGPT in 2023, a study measuring developer productivity showed an immediate 50% drop in productivity. This was measured across 8,000 GitHub users and their release events. (A release is a software project deployed to a wider audience.)

• However, this trend was reversed two days after the ban, back to normal levels, and it’s not why you think.

• They noticed a sudden increase in using VPN and Tor tools to circumvent the ban (it lets you pretend you are accessing the internet from another location)

• Surely, a well-intended restriction to protect data and privacy was also a good experiment to see how established GPT tools already are - https://arxiv.org/pdf/2304.09339

We are past the point where we would say that AI is a fad

A Slack research study earlier this year revealed some mind-boggling numbers if you think about how nascent this technology still is:

• AI use in the workplace accelerated 24% in Q4 2023 — 1 in 4 desk workers reporting they have tried AI tools for work (Jan 2024)

• 80% of those using AI say that it is already improving their productivity

• Desk workers who have defined guidelines for AI use are six times more likely to try AI tools than those who do not

• Opportunity: Desk workers think 41% of their work is on tasks with low value, repetitive or lack meaningful contribution to their core job function.”

• And the go-ahead from the top: nearly all executives feel pressure to integrate AI tools into their organization

So, we all agree that introducing AI to the workplace is a good decision.

But HOW?

The adoption gap…

Why can’t we “just” start using it?

Here is the problem: Our calendars and to-do lists leave little room for experimentation with the new.

Sometimes, we can barely get our lunch in and must finish it throughout meetings. It's like the corporate Hunger Games: constantly fearing somebody might start talking to us mid-bite and everyone will recognize that we smeared mustard all over our face. I digress…

Aside from the “write this email for me in a professional tone” prompts, we must find extra time to understand and learn to use it for our specific roles. But we are not sure what our company’s guidelines are. And then there is the risk of the models not being accurate enough.

Executives need to consider another gap: the fear of data security, privacy, and AI accuracy, in addition to a long list of compliance questions.

To solve this, new responsibilities emerge and with it, a new role.

New responsibilities emerge

Imagine a person solely responsible for optimizing a workplace using AI. They are new hires with empty calendars, ready to tackle this new opportunity head-on. They can look for and find all these low-end, tedious, repetitive tasks AI could take over for us. And establish a set of guidelines for the whole company that makes everyone feel comfortable exploring.

Let’s call the role: AI business technologist

• Spearhead company AI guidelines by working with senior leaders, legal and data security teams.

  • As we know, this increases the likelihood of workers experimenting with AI by 6x and sets them up for increased productivity.

  • It can help address executive concerns like data security and privacy, AI accuracy, and compliance.

  • It can define how to validate AI and avoid low-accuracy responses.

• Build a company-specific knowledgebase around AI and which business processes AI can be deployed in.

• Define AI integration milestones.

  • Long-term initiatives vs short-term wins

  • Integrate long-term needs into technical roadmaps.

• Develop a data landscape and identify gaps that prevent us from deeper integration.

  • AI lives on data. If the datasets are not in a form AI can consume, the first step must be to find data gaps and a path to making them AI-ready.

Two paths for companies to increase AI adoption

Now that we know the responsibilities, what can companies do to get the work started?

Path 1 - Hire Consultants

• Consultants come in with an empty calendar and focus.

• They will interview your teams to understand workflows, problems, and the current state of the business.

• They will propose a set of milestones for implementing AI.

• 👍Pro: Quick turnaround, internal teams can stay focussed on existing projects, temporary engagement with clear deliverables and timelines, already specialized, and bring knowledge.

• 👎Con: Consultants are expensive, and the expertise will not remain in-house. There is a risk of becoming too dependent on consultants in the future.

Path 2 - Grow AI-expertize in house

• Foster internal development of this AI-business technologist role

  • Long-term strategic value

  • Either hire for it or grow existing employees into it

  • 👍Pro: Open up new career paths for your teams and build in-house expertise. They already have internal knowledge and relationships.

  • 👎Con: What happens to their other priorities? Can they juggle both? Will other initiatives slow down? The new hires would require a new budget to commit to without a clearly defined outcome.

And this brings me to my last point…

This is where a new career opportunity evolves.

Career Opportunity: This is what you can do to become your company’s AI expert

These steps will not require you to learn programming or dive deep into the intricacies of AI. This will be a springboard to show your company that combining you and AI can bring value.

Feel free to save this version:

Or copy and paste the steps below:

1. Carve out time to educate yourself on AI

2. Find connections between your work and how AI can help specific workflows

3. Pitch your interest in AI to your leaders

4. Tell them that you have been playing with AI and have a few ideas on improving your companies’ workflows.

5. Ask if you can spend a few hours with other departments - maybe your leaders have a prioritized list already.

6. Understand the workflows and look for repetitive tasks that could be optimized with little effort and the proper prompts.

7. Document every single step of how you would improve the workflow

8. Collect data from the specific department you are targeting and understand how much time it would save them

9. Write down a full documentation of your improvements and share it with senior leadership and across your company

10. Try to extract a framework so that it can be reused across other functions

It’s a great time to seize the opportunity if you want to grow into an AI career. I would love to hear back from you if this is a framework you would apply.

If you think this would be valuable for someone you know, please pass it along. It would mean the world.

Have a great rest of the week,