Considerations of AI for Knowledge Workers

At Thriveal, we lead a lot of very smart people who lead knowledge firms. Their main work in their firm is the creation and selling of knowledge. There are many knowledge workers in many different disciplines: developers (those who code), lawyers (those who interpret the law), doctors (those who interpret symptoms), firm owners (those who produce tax, financial, and advisory solutions from financial data), and even designers (those who interpret the world and economy graphically). These knowledge professions are being, and will continue to be, impacted by the rapid changes around Artificial Intelligence and the tools that are embedding this technology.

Many professions, such as manufacturing, construction, and the trades will also be disrupted but perhaps not at the pace that knowledge workers are being disrupted right now (I’m unsure about those professions but I’m sure it is impacting them now as well). We need a way to think about this rapid disruption, as many are wrestling with what to do and how to respond in a way that makes sense for knowledge firms and the services that we all sell. 

We could think of this rapid change in terms of concessions: that is, where do we have to concede to AI technology in our knowledge work? Even though it does seem to be coming that our work will look different as we partner with AI, that is really looking at this change in our world from the wrong perspective. A better question is “what great new work do we get to do now?” Instead of focusing on what’s being given up, we can focus now on what we get, what better ways can we design our work for the future, what new services will we offer that we don’t offer now, and where will we become more valuable now that AI has entered the scene?

I asked some AI tools to define themselves:

“ChatGPT, define artificial intelligence in 2 short paragraphs”

Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks that typically require human intelligence. It involves the creation of algorithms and models that enable machines to process, analyze, and understand complex data, make informed decisions, and learn from experience. AI encompasses various subfields such as machine learning, natural language processing, computer vision, and robotics.

Machine learning, a prominent branch of AI, focuses on enabling machines to learn and improve from data without being explicitly programmed. Through the use of statistical techniques and algorithms, machine learning algorithms can identify patterns, make predictions, and provide insights from vast amounts of data. AI has a wide range of applications across industries, including healthcare, finance, transportation, and entertainment, and continues to advance rapidly, opening up new possibilities for automation, problem-solving, and enhanced decision-making.

Google’s Bard’s response is quite different and further citing sources for its responses and other suggested searches.

“Bard, define artificial intelligence in 2 short paragraphs”

Artificial intelligence (AI) is a branch of computer science that deals with the creation of intelligent agents, which are systems that can reason, learn, and act autonomously. AI research has been highly successful in developing effective techniques for solving a wide range of problems, from game playing to medical diagnosis.

AI is a rapidly evolving field with the potential to revolutionize many aspects of our lives. As AI continues to develop, it is important to consider the ethical implications of its use. For example, we need to ensure that AI is used in a way that is fair and does not discriminate against any particular group of people.

The world has been developing AI for many years, and now it is in the forefront with the massive power of LLMs (large language models) to aid knowledge workers in their daily work. But like many rapid changes like this to our economy, profession, and world we have to stop to make sense of it and how we will interact with these exciting new tools. This article is meant to give a sense of how we are applying this thinking to our own firm and team at Blumer CPAs.


AI is here to stay and it will change the world as we know it (much like electricity or the printing press did, as highlighted in this great podcast on the subject). Though we will have to concede the use of AI in places we have historically owned or managed as humans, we get to do it with the human care that makes our profession so strong and valuable. As professional knowledge workers, I can think of a few areas where our work needs to change (tackled in the form of questions below):

Transparency – what part of our use of AI should we disclose to our team, clients, and our market?

  • The contrarian question is to ask which part of our use of AI can we decide NOT to disclose?

Work-sharing – what part of our great work should we now share with AI, allowing it to do some of our heavy lifting?

  • The contrarian question is to ask what part of our work should we produce concurrently out of our own minds?

Liability – as a licensed and regulated profession, what liability do we carry when we leverage tools such as AI (and the many iterations we find it like in note taking, transcription creation, meeting summaries, etc.)?

  • The contrarian question is one of risk: where do we take risks because we believe there is a low liability in various uses of this technology (knowing that the risks have not all been defined or even considered yet)?

Protocol and policy – what principles can we put down in our firms that will further guide us in our future use of AI as it is rapidly developed and deployed into our world?

  • The contrarian question is to ask what should we seek to NOT define right now as we let the development of AI continue to excite us and guide our future work?

There are probably many other considerations, but the ones below are defining our own firm’s thoughts around this exciting technology and the concessions we are making in relation to the use of this technology. Since we hire smart people, we are going to take a few weeks to have our team break out into Zoom groups and discuss these topics and our firm’s considerations to develop our best practices & policies:

  • Discuss appropriate AI use in team meetings, sales calls, coaching/consulting, client messaging and client permissions for transcripts, OUR permissions for transcripts clients capture, liability issues, confidentiality considerations, security considerations, etc.
  • Discuss using Loom for client-facing processes, criteria & best practices (e.g., not diluting white-glove service, keeping things personal, expand uses in advisory, portraying our firm as professionals with communication, etc.)
  • Discuss using Zoom meeting recording AI tools for client-facing processes, criteria, best practices + knowledge capture. (e.g., creating internal efficiency with action item assignment, creating a library and Twist thread of link posts, external use without losing our brand voice, leading as an expert, white-glove service, personality of each team member and the firm, etc.)
  • Discuss how to create meeting notes from our AI tools: can we label in the AI tool for a library, post links only in our chat, or possibly extract and tag names for action items and ClickUp capture, etc?
  • Discuss how to clean up/send notes/action items to clients after our AI tool takes notes and creates the summary transcripts to retain our personal touch and authentic voice.

Give us some comments on how you are deploying AI into your firm, and the considerations you are making.

Jason Blumer

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