“100% of this article was written by a human” (True)
We’ve all seen large language models (LLMs) rapidly move into the mainstream, and many of us are already using them at present to generate blog posts, sales emails, and marketing campaigns (sadly, not yours truly).
Indeed, there is no shortage of ideas and blog posts explaining how businesses will use LLMs to generate content and remove routine or laborious tasks. Some say LLMs will render coders and lawyers obsolete. (BTW, they won’t). While there will certainly be job disruptions, we believe the change will be one of radical productivity improvement and, as a result, much more interesting and fulfilling work for many of today’s knowledge workers.
Before continuing, let’s clarify. LLMs are just one type of AI, a “tool.” If you think that auto-creating a sales email is a kind of “meh” endgame of billions of funding, you won’t hurt our feelings. That’s because we feel the future of AI in business will be utilizing many AI tools that will go far beyond creating content. They will help you think and take action. They will help you do things that are almost impossible or are very expensive to do today.
If you love manually updating JIRA with bug reports, typing QBR results into spreadsheets every Friday, or getting five people in a room to discuss your best customer, then the adoption of AI for your business is going to be a bummer. For the rest of us, AI will make us much more productive, informed, and, ultimately, employable.
Before continuing, I would like to say that I have spoken to many companies that have “started using AI in our business.” This always means dumping a healthy serving of emails and support tickets into GPT and generating summaries. And many now say, “That was cool, but now what?”
They’ve just scratched the surface. At the risk of sounding like an AI hype machine, answering “What’s next?” is really difficult because we’re still trapped in an impossibility box: today, there are things we think are impossible but aren’t anymore.
At Sturdy, business for AI will go beyond Generative AI, fundamentally changing how businesses collect, organize and synthesize their information. For now, I will call this AI Harmonization (AIH). Again, this goes far beyond writing sales emails. Beyond the LLM, AIH will illuminate previously dark sources of data and harmonize that information across other models, thereby creating previously unimaginable strategic visibility and scale.
The pieces of this AIH pie are the following:
Of course, what I just laid out vastly simplifies the challenge. Yet, I can’t help but feel super excited about what it means…here are some examples:
If you are an Account Manager, your day might start with,
“Here are three accounts you need to look at right now.”
Or, let’s say you’re a VP of CS,
“Let me know anytime an enterprise customer has an issue within 90 days of their renewal date. Check this every day at 9 am.”
Or, imagine being a new VP of Products at a SaaS business,
“Every Tuesday, send me an XLS with a product roadmap with all bugs, organized by topic, reported by our enterprise customers worth more than 500k in ARR ranked by unhappiness generated and estimated engineering complexity.”
Sure, many of the examples above are already completed in many well-run companies today. They are just being done with manual labor. A lot of manual labor. In fact, our Sturdy data shows us that as much as 45% of an Account Manager’s day is data entry. Logging tickets, updating salesforce, writing call summaries (that number doesn’t even count the “account review” meetings).
Yes, AI will eliminate almost all this manual labor masquerading as knowledge work.
It will automate almost all data collection… reporting…and, eventually, much of the response.
But, worker productivity will skyrocket and allow our teammates to focus on much more meaningful tasks.
(Shameless plug: you could buy Sturdy today and next week 3 of the examples shown above are now part of your business. (What, you think I write blog posts for my health?))
In short, the people interacting on a day-to-day basis with customers will have about twice as much time to do high-value things, like talking to customers. If I had to guess, I would say that this probably means companies will have fewer Account Managers, but it also means that they’ll become twice as valuable (because they’ll be 2x more productive).
If you were hired as an Engineer in 1970, it is likely that for the first decade of your professional career, you spent your days using a slide rule to double-check someone else’s work. Did a computer take the engineer's job? No. Did their jobs get better, more productive, and more important? You betcha.
Let’s do this.
Often lost in this discussion of AI technology is the discussion of its impacts on our teammates and coworkers. What does the widespread adoption of AI in business mean for the careers of people who work at these businesses? While many of us are, and should be, concerned about job destruction, I want to talk about job creation.
In today's digital age, the sheer volume of data generated by businesses is staggering. Ironically, most of this data is unstructured and trapped in things like emails, support tickets, and phone calls. Until now, this meant that the only way to extract valuable insights was by using manual labor to categorize them.