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Updated: Oct 3, 2023

We are in the early stages of the fifth technology wave personally experienced by many of us (#1 personal computing, #2 internet, #3 mobile, #4 cloud/api-ification). Use this as a catalyst to improve your business's data and technology stack to best of class and thoughtfully integrate AI into your strategy and execution plans.

Jennifer Stewart, Managing Partner of JSTAR Holdings, contributed as a panelist at the Northeast Movers and Shakers "AI Pain Points, Perks and Strategies" Event last week, with fellow executive panelists from McKinsey, CyberSecOp and On Pepper (and sponsored by Bridge Bank and Lockton and hosted by Opus Connect, Holland & Knight LLP, Young American Capital and BBC Advisors). Key takeaways below.


Machine learning artificial intelligence (ML AI), with a focus on using data and algorithms to imitate the way humans learn and continually improve its accuracy, has been with us for decades. Thousands of companies have deployed ML AI, primarily on structured data, with well known applications including Amazon's and Netflix's recommendation engines and advances in self-driving cars. The innovation by Google of the transformer in 2017 set the stage for the Generative AI that is currently grabbing all the headlines, powered by closed Foundational Large Language Models (LLM) from OpenAI (ChatGPT 4.0), Google (PaLM 2 commercialized as BARD and upcoming Gemini), and Anthropic (Claude 2) as well as open source LLMs such as Meta's Llama 2.

JSTAR's key macro takeaways related to Generative AI:

1. Generative AI is a transformational technology tool and potentially bigger than the advent of the PC, internet, mobile phone or cloud. There will be big winners as well as losers, and the trajectory will not be a straight line or necessarily obvious.

2. We are in the early innings. There are literally new groundbreaking developments daily, and what we have access to in three years will look very different than what is available today.

3. Reliability and accuracy is still in its infancy. The ability to securely unite proprietary data (and keep it confidential and controlled) with LLMs at scale, is just beginning to fall into place. Over the next couple of years there will be a huge number of specialized SaaS services by industry verticals and functions complementing the many services available today.

4. AI inference of business data (both structured and unstructured) can make a lot of difference and meaningfully contribute to growth, efficiencies, customer service and real time automated customization.

5. Computational availability is constricted and costs currently very high. These costs will drastically reduce over time assisted by Moore's Law and other technology efficiencies.

So what does this mean for your middle market business?

1. Recognize that AI can power expanded capabilities, but it is just another tool in your tool box to use to effectuate your strategic and execution plans.

2. Understand your key growth, profitability and competitive advantage drivers and begin strategizing how both structured and unstructured data pools (both proprietary, purchased and non-proprietary) can be leveraged using both ML AI and Generative AI to have an outsized impact on your key drivers. Also determine what implementation options, costs and time would be.

3. Keep abreast of developments in the industry and define when it makes sense for your business to make the AI investment. Different businesses and strategies will have different answers and the AI industry is moving very fast. And there will be many more customized industry and functional AI SaaS services (that are safe and can protection your data) for implementation within a short period of time.

4. Whenever you start, start with a manageable clear goal, test extensively to make sure the results are safe and reliable, and then build on the learnings from the implementation and results.

5. And at a minimum, begin encouraging your leadership and key functional areas to carefully experiment and begin to get comfortable with low risk but administrative efficiency enhancing AI tools, such as ChatGPT and its plug-ins to help create first draft research, blog or social media posts; CoPilot to write first drafts of emails or powerpoint;, for example, to take first draft meeting notes, summarize and create action item follow-ups; plug-ins to support automated and customized LinkedIn communications; Canvas and DALL-E as content creation tools; maybe Cody, for example, to streamline programing; etc.

There is one thing that we know to be true about business - a company is either propelling itself forward or falling behind. Embrace the exciting opportunities today to continue to transform your business and best serve your customers, employees, suppliers, communities and stakeholders!

Looking for a capital partner or buyer for your business? If so, contact JSTAR. We understand the complexities of business and are ready and motivated to work symbiotically with you to provide #CapitalToGrow, #RefineStrategyAndExecution, #CatalyzeThoughtfulEfficiencies, #FixBottlenecks and #MakeLifeEasier for you and your customers, leadership, workforce and suppliers.

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