How business owners will adapt to AI

Business owners are actively seeking AI solutions that will transform their organizations forever, are easy to implement and free. Our expectations may be a wee bit unrealistic.

Over the last several months, artificial intelligence (AI) has transitioned from a theoretical threat to humans to an endless array of real-world applications that businesses can implement right away. Yet, we also need to be practical. It’s dangerous when we set unrealistic expectations for technology because users will revolt, which slows adoption. It’s an opportune time to reevaluate the current state of play in AI.

We know our choice is to implement AI or compete with it. However, given our lack of understanding about it, we all need to start with a real-world evaluation of our risk tolerance. Management teams should attack this complex problem by evaluating it in stages, considering the long-, medium- and short-term impacts, and then consider the investments they are willing to make.

Source: Marc Emmer – Vistage Presentation

Short-term use of LLMs

While large language models have the fastest adoption of any tech in the history of man (except for TikTok), our acceptance is notably slow. Most companies are just tinkering today. Consider the evidence: only 5% of ChatGPT users are paying for a 4.0 subscription, even though it unlocks all the power, including custom GPTs (think of custom GPTs as a tool that turns anyone in your organization into a coder, creating automations and utilities in minutes).

GPTs have become table stakes. Other free LLMs have recently gained favor, including:

Perplexity: Ideal for internet searches and feels more like a web browser than ChatGPT. Use Perplexity for content generation, white papers and R&D.

NotebookLM: Useful for conducting research, analyzing and summarizing documents. Use it to write SOPs, employee handbooks and work instructions.

The Midpoint: 2025 is the year of the agent

Most Small and midsize business leaders are looking for more from AI, and the innovations currently being unveiled are known as “agents.” Agents, unlike the algorithmic technologies that preceded them, are end-to-end workflows that complete many steps without human oversight. For example, AI could manage the entire employee onboarding process through repeatable steps, including completing a job application, conducting a background check and assigning passwords.

While such systems exist today, they generally require a human (such as an HR generalist) to shepherd tasks separately, whereas agents can talk to other agents to unleash a wave of automations. While the HR professional is necessary to monitor the automations, the hiring process can be accelerated at breakneck speed. Instead of “boiling the ocean”, companies should look for entire processes they can automate through end-to-end workflows, managed by AI agents.

The Golden Goose: Business Transformation

Leveraging AI’s transformative nature will require that we think bigger and invest more. AI represents perhaps the biggest business opportunity in our economy’s history — bigger than the gold rush or internet boom. It provides an opening to build entirely new business models that provide customers with unique value. How?

Companies that have already harvested AI are using a “digital core.” There are no operating employees in their critical path of activities. For example, imagine creating a new QuickBooks account. The user would sign in, add a credit card, and upload information without any human support.

However, reaching this pinnacle takes time. Many AI leaders have achieved scale through network effects. But this critical mass requires money and investment because it’s costlier to automate something than to complete a task manually until you achieve enough volume to warrant automation.

We will use AI in ways we can’t imagine, including creating business strategy and measuring results. The ultimate competitive advantage is using AI to predict the future—the essence of predictive modeling. Today, our firm spends every waking hour developing these tools so that SMBs and their leaders will be positioned to use them.

Imagine you operate an ice cream shop and need to know how much product to buy, or how much labor to staff. Models inform on events in the area, the weather and traffic patterns, and predict what you should sell every day. Applying this thinking to private companies, we can forecast demand and create strategy based on real-time information.

We also need to be realistic, because changing a business overnight will require investment in AI and cloud infrastructure. These solutions will be managed by the most expensive workers in our economy — edge engineers and data scientists who may cost $300k per year, which feels out of reach for many small and midsize businesses.

So, we must walk before we run. Begin with creating an AI strategy for your company that considers long-, mid- and short-range impacts on your business today while preparing for transformation in the future.

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