Solving your GenAI problems
For professional services, the modus operandi has always been to stay ahead of trends for clients. That means GenAI has become a near constant presence in briefings, podcasts, forecasts and pitches. But, as LINAR Consulting’s Sam Stamp cautions, some remain stuck gathering digital dust.
Solving your GenAI problems
For professional services, the modus operandi has always been to stay ahead of trends for clients. That means GenAI has become a near constant presence in briefings, podcasts, forecasts and pitches. But, as LINAR Consulting’s Sam Stamp cautions, some remain stuck gathering digital dust.
There are still people in professional services who haven’t engaged with GenAI tools on a practical level. They may have dabbled but found it not as useful as they thought and so left their Chat GPT bookmarks gathering digital dust.
For clarity, when I refer to GenAI I mean advanced artificial intelligence systems capable of creating new content, such as text, images, audio, and video, that mimic human-like creativity and intelligence. In particular, I have in mind the major Large Language Models (LLMs) such as ChatGPT, Gemini, and Claude.
I believe, with these tools leading the way, we are on the cusp of foundational change for the world of work, and perhaps for humans. There’s a whole world of writing on this, but a recently trending thought-piece can be found here (it’s rather technical, but fascinating).
However, certain advancements in models and tools are still needed for this monumental shift, and this gap has likely contributed to the understandable level of scepticism and disappointment. However, anyone not engaging does so at their own risk.
Personally, I use OpenAI’s GPT-4o (Omni) model multiple times a day, finding it additive and productivity-enhancing. This perceived benefit has created an “AI-first mindset”, where I often turn to GPT before I turn to Google. This habit helps me come up with new ways to make use of the tool - as well as to understand and appreciate its limitations.
I recommend this mindset and, to help you begin to foster one of your own, I have started to break down some of my own most common uses of GenAI into categories that anyone can apply to their work, starting right now.
Blank Page Problems
The hardest part of writing anything is staring with a blank page. By giving an LLM some context about what you’re writing and an unstructured stream of consciousness with your initial thoughts, you will get something back that can immediately be worked on. You don’t necessarily need to use any of what you get back but it will drastically increase speed-to-productivity.
Example prompt: Give me some thought starters for a blog I need to write about the impact of behaviour change programmes on tech adoption in large organisations. I want to focus on the importance of the human side of transformation rather than just the technical. The audience will be mid-level professionals at consulting firms.
“With these (GenAI) tools leading the way, we are on the cusp of foundational change for the world of work, and perhaps for humans. However, certain advancements in models and tools are still needed for this monumental shift, and this gap has likely contributed to the understandable level of scepticism and disappointment.”
Knowledge Problems
LLMs are not search engines and they can hallucinate (make up answers) but they are incredible at explaining general concepts. About to start working with a pharmaceutical client but have no idea what Pharmacodynamic Modelling is? Ask GPT (FYI, it’s the biological effects of a drug on the body and its mechanisms of action). Yes, you may need to check some specific facts but it’s great at getting you up to speed.
Example prompt: Explain Pharmacodynamic Modelling to me in a way I could understand. Assume I don’t know much about pharma! Ask me a question at the end to see if I’ve got it.
Consolidation Problems
If you have a large amount of content, copy or data that you need to compress - for example due to word count or formatting constraints, you can ask an LLM to do it. You’ll get a result in seconds. Be sure to clarify what elements can change. Does the tone need to stay the same? Are there any keywords that must be retained? The same thing goes for format changes. Provide an example of the structure you need and you can turn a blog into a press release or a podcast script into a series of LinkedIn ads.
Example prompt: Retaining the opening and closing paragraphs, reduce this blog by 100 words. Ensure all capitalised references are kept as they are and maintain the same tone of voice.
Summary Problems
Like the previous case but more useful for content that isn’t yours to start with. LLMs can summarise articles and research papers. By providing specific guidance on what elements you are most interested in, you can get through multiple articles in the space of a 15-minute ‘research session’. This also gives you the extra space to spend more thinking time on the one or two pieces that seem most relevant or interesting to you.
Example prompt: Tell me the main points of this article. I’m particularly interested in any elements relating to the legal sector and implications of AI on the practice of law. Give me the summary in bullet points, with specific references to the text.
Personalisation Problems
This is particularly useful in a sales context. If you have nailed the key messages for a particular piece of outreach but want to tailor it slightly to multiple recipients you can input the key messages and instruct the personalisation you require. You’ll receive as many slightly tweaked versions of the same email as you need. A note on privacy concerns here - it is best practice not to use specific names or email addresses.
Example prompt: Give me four versions of this email, changing the first line to reference either the pharma, healthcare, media or finance industries. Leave space for me to add individual names and organisations
These examples only scratch the surface of what one can do with an LLM but if they even save you 30 minutes a day (they save me considerably more), you can use that time to come up with more use cases that are more tailored to your own work.
Helping individuals and business services organisations figure this stuff out is exactly what we’re setting out to do at LINAR. Bridge the initial gap between promise and practice, helping people to get from the beginning of their GenAI journey to a point where they can use different tools and start to make informed decisions about a future-facing strategy. After many decades of combined experience in the sector, we know it can be done better and genuinely believe this new technology is a pathway to more enjoyable and effective work.