Five AI questions we get asked most often
You’ve probably heard of (or used) AI transcription tools like Otter, Wudpecker and Fathom.
Having more rich meeting notes means we have more data about questions we’re asked and how we answer them. It allows us to track trends, revisit points of view, and identify recurring themes.
This week, we wanted to write an Edition that compiled all the frequently asked questions we get about AI from clients, colleagues and partners. The old way would be to do some desk research, have a team discussion and compare notes. The new way is… we just ask the data.
For this article we asked Otter Chat – the AI feature in Otter.ai – what questions about AI we were being asked most frequently. We then asked ChatGPT to pick out the themes and synthesise the most frequently asked questions, and what our answers were. Then we checked the results and copyedited them to make sure they were on point.
Five AI Questions
1. I want to use AI with my team, but they’re skeptical. How do I persuade them?
Scepticism about AI is a good thing. If someone isn’t a bit sceptical, they’re probably trying to sell you something. Either that or they’re at the peak of Mount Stupid.
It’s never a good idea to defend AI as a whole - it’s too big and amorphous. Focus on specific, demonstrable applications and benefits.
AI can be used as a powerful tool for managing complexity in the modern workplace, potentially making work more enjoyable and productive. But, it’s not magic. It’s a physical technology that requires energy and computing power. Understanding its real-world nature helps demystify it.
Framing AI within the context of digital transformation, and as a chapter in an ongoing technological evolution can situate it as part of a natural progression rather than a disruptive force.
Demonstrating AI through hands-on experiences often makes the strongest case, allowing sceptics to see the tangible advantages firsthand. Furthermore, AI literacy and ethical oversight are crucial, addressing concerns and fostering a common language within organisations that can bridge gaps in understanding.
2. In what ways could AI replace traditional software in corporate settings?
AI can streamline and enhance various functions – often replacing traditional software. It automates tasks like generating meeting notes, managing emails, and performing data analysis. In CRM, AI anticipates customer needs and personalises interactions, while in project management, it streamlines routine work. AI tools, such as those in HubSpot, can reduce repetitive processes like data entry, allowing teams to focus on strategic initiatives and direct customer engagement.
3. How can AI simplify [insert complex or time-consuming task here]?
The best way to use AI to streamline and simplify is by firstly focusing on automating the most repetitive parts of the process. This is often something like data entry and report generation.
AI can be brilliant for anything where you’re using your own personal expertise and experience to evaluate things – like whether or not to go for a pitch for example – or where you have to analyse a large amount of data for insights.
We have a simple, three-step method for using AI to tackle big tasks:
Problem statement
What is the challenge we are trying to meet. A problem statement is a concise description of an issue or challenge that needs to be addressed. It clearly defines the gap between the current state and the desired state, providing a foundation for developing solutions and guiding the problem-solving process.
Task breakdown
A task breakdown is a detailed list of specific activities or steps required to complete a project or solve a problem. It involves:
◦ Identifying all necessary tasks and subtasks
◦ Organising tasks in a logical sequence or hierarchy
Execution plan
Estimating time and resources (time, people, data, tools, examples) needed for each task, and where AI tools could speed you up. Delegation is a good analogy.
This method helps you to know where you can use AI at each step of the process rather than trying to tackle the big complex challenge at once.
4. How can AI tools help alleviate anxiety related to information management?
AI can help to quickly access information by summarising large documents, making complex information easier to understand.
Based on the conversations, here are some ways AI tools can help alleviate anxiety related to information management:
Organising data, creating searchable systems, and summarising documents.
Breaking down large projects into manageable tasks and automating routine work.
Enhancing decision-making and drafting communications to reduce stress. AI tools enable more structured and efficient data handling, reducing the cognitive load associated with complex tasks.
5. What does AI literacy mean, and how is it different from simply learning software?
There are two main differences.
Software generally behaves as you would expect it to, whereas AI will give you a different response every time you ask a question. And in this way, working with AI is more like learning a language than learning a software system.
AI is a cognitive tool, as well as a practical one.
For these reasons, you get used to working with AI in a different way as traditional software. And to learn to use it effectively requires you to develop a whole new skill, one we call AI literacy.
AI literacy extends beyond traditional software skills, it requires an adaptive and critical approach. Rather than following a procedure correctly, AI literacy involves understanding the limitations and potential of AI, using it to augment human intelligence in creative ways.
At the moment, we’re in a period where the uses of AI are still being discovered. So focusing on fluency in applying AI across various contexts rather than mastery of specific features.
