AI is rebranding efficiency as growth

Over the years, I have become a student of branding. I am mesmerized by rebranding stories – from Twitter-to-X to Facebook-to-Meta, Dunkin’ Donuts-to-Dunkin’ and even Kentucky Fried Chicken-to-KFC. I find it compelling to watch the rollout and then attempt to decipher the underlying business strategy.

So, when The Monitor recently reported on rebranding in the equipment finance industry, I was more than a little intrigued: Why are more independent commercial finance companies rebranding as private credit? As the article points out, rebranding involves more than just logos:

“…independent finance companies are now branding themselves as “private credit” lenders. This rebranding isn’t just a matter of semantics – it’s a strategic move to reframe their value proposition in a marketplace….”

A brand is a promise, so changing involves the company mission, objectives, and how results are achieved - a change in how business gets done.

Efficiency isn’t a business, but it definitely has a brand promise in the hands of operations experts: “Get things done cheaper.” Efficiency is in the news with the administration’s new Department of Government Efficiency (DOGE), and the efforts are all about cost-cutting. In the case of DOGE, the cost focus is appropriate because the overall objective isn’t “growing government"; it's getting the same things done for less. However, growth is always the primary objective of a business, and every good entrepreneur knows that one can't cut more than one's spending, so the business impact is limited. Bill George, former CEO of Medtronic, once commented on the impact of operational efficiency leaders: “… they were just cost cutters. And you can’t cost-cut your way to prosperity."

Enter the efficiency opportunity of AI. AI promises to do its job, whether making decisions, writing letters to customers, or answering invoice questions faster than any human. Even if it’s not always right, it will save time because it will be wrong more efficiently than humans. One might say that AI’s brand is efficient, but well-implemented AI is going to create new business value for efficiency because its job will be more than just cost-cutting.

At this point, AI is, by definition, an investment. Every business leader engaging in AI today is investing in their business. If they aren’t investing in new data infrastructure to consolidate and organize their data to use with AI, they are paying data scientists to use the AI tools native to their cloud provider to train and test machine learning models that will implement AI-based workflows. Investments are made to provide a return in the form of improved performance and/or outcomes. Choosing the right outcomes for AI to produce more efficiently will improve and grow the business.

AI is a prediction technology, and its purpose is to predict outcomes – all possible outcomes to a given question or process –. GenAI, built on Large Language Models (LLMs), learns how to predict the next letter, word, pixel, number, or phrase and eventually answer a prompt. Operational AI, built on models of the historical outcome data of the business, evaluates and quantifies the probabilities of the future outcomes for a workflow decision: approvals, funding, payments, etc. When the decision is assisted or automated by AI, that action becomes, as Marc Benioff calls the efforts of one of Salesforce’s agents, “an output of work.” Outputs of work drive business results; they increase the return of the inputs. More units of output from the units of input is productivity. More efficiency with the inputs – labor, time, capital – produces a greater number of outputs and grows the business.

The table shows some “outputs of work” that AI can perform more efficiently in an equipment finance workflow. Some of the “conversations” in isolation appear to be simple cost savings, but when considered in aggregate, the higher workflow efficiency supports a more deals, more profit, and access to more capital. More capital added to the existing technology and labor investments grows the book of business. AI delivers efficiency that drives productivity that drives growth.

AI efficiency raises the productivity curve, creating opportunities for growth with additional inputs.

Because AI is always expected to be faster than humans, it’s natural to expect it to provide efficiency. Some, the operationally minded, like the DOGE team, will naturally look for AI to be a cost-cutting tool, but this will be a mistake because cost-cutting is bounded. AI is an investment and, as such, should be a tool that improves returns. Exponentially higher returns as more productivity in one part of the workflow can bring more input to another. Higher efficiency in deploying capital can generate multiplicatively more capital.

This one, I understand. AI is rebranding efficiency as growth.