How to boost productivity at work and make generative AI work for you
How to boost productivity at work and make generative AI work for you
Research conducted by the company behind ChatGPT, Open AI, concluded that 80% of workers in the US could see at least 10% of their work automated in the near future. Similarly, a report published by Goldman Sachs in late March 2023 predicted that 300 million jobs worldwide will be affected by generative AI. The report also noted that, while some job losses would be inevitable, adopting AI could increase productivity in the workforce.
Due to its nature, this wave of automation is going to impact white collar workers more than ever before. So how can you futureproof your career and ensure your services remain in demand?
Embracing generative AI could enable you to use it to your advantage and be more productive in your role. In this blog, I’ll be explaining how you can get the most out of tools like ChatGPT and outlining the skills to develop, allowing you to stay ahead of the curve.
Five tips for increasing productivity with generative AI
1) Think about what you need it for
Which tasks within your role could be automated? Before GPT-4’s release, much of the focus on generative AI’s capability in the workplace had been on copywriting. However, the potential for these tools is fast expanding. For example, they can help you plan presentations, or create and populate spreadsheets quickly with original formulae.
What about as a research tool? The primary function for chatbots was to generate the information you need, and in a format that suits you. There are potentially errors in what it provides, but that is fast improving. The development of Google Bard and Microsoft Bing’s own product means that the gap between AI chatbots and traditional search engines in terms of reliability is closing.
2) Add the right plug-ins
One of the big advancements that came with the launch of GPT-4 was the release of plug-ins that open up a host of new opportunities. You can summarise conversations and draft responses on Slack, analyse real-time data on FiscalNote or generate meeting summaries from Zoom. Meanwhile, the Zapier plug-in allows you to integrate the tool into Microsoft Office, Google Suite, Hubspot and Facebook Ads, among others.
Of course, it’s important to think about the legality and security surrounding this, particularly if you’re accessing or sharing sensitive data from your organisation. However, these all have the potential to save you time and provide useful assets and insights.
3) Get your prompts right
The great thing about a large language model (LLM) is that making a request is intuitive, and we receive a response that’s easy to understand. You don’t need specialist technical skills or knowledge to get started.
To really reap the benefits of ChatGPT and other generative AI, though, you’ll need to perfect your prompts. In fact, there are already businesses hiring prompt engineers to coax the most useful content from these tools.
However, just because we’re seeing examples of this being a responsibility in itself, it doesn’t mean you can’t get involved in your current role. There’s a lot of advice out there on getting your prompts right, which I recommend you look into. Some examples of things you can do include:
- Be clear in what you want – the best prompts are the ones that clearly define what the output should include, the format it should take and how it will be used.
- Defining a specific audience for the output – this will tailor the response so it targets the right people.
- Try multiple prompts – refine the wording of your request will land more suitable output.
- Break down any requests for longform text into several requests – doing this will make it easier to rewrite or change any sections.
- Use reverse engineering – Working on a presentation or pitch? Why not ask ChatGPT to predict any questions from the audience? You could even ask it to suggest the answers. Alternatively, create an agenda for a meeting by thinking about the attendants’ needs.
4) Optimise the output
When using an LLM for fact-finding, double-check the results it provides. You could even do this by focusing on one piece of information that you’re unsure about, and asking the chatbot about that specifically. Again, breaking down your questions can help to provide a clearer picture.
As for copywriting or coding, even after multiple prompts and concise briefs, it’s unlikely that generative AI will give you content that’s good to go. Rewrite anything that doesn’t fit your tone of voice, or check the data on your spreadsheet for mistakes.
To be more productive in future, think about how you could improve your prompt for next time so that the output is closer to what you need.
5) Stay up to date on trends
The above tips will give you a head start in making generative AI work for you. However, these tools are evolving constantly, and they’ll soon be able to take on even greater responsibility. The truth is that, if you don’t keep up with their capabilities, you won’t be as productive as possible, and that could put your position in jeopardy. ChatGPT and similar models are here to stay, so you need to be able to use them properly.
Which skills will help you use ChatGPT and other generative AI?
As I mentioned above, you don’t need to rely on technical skills to use an LLM or many other generative AI models. That said, those who develop their “soft” skills will be the most productive. For example:
- Creativity: Given the capabilities of generative AI, we’re getting to the point where the only limit of what it can do is the user’s imagination. Thinking creatively about how to approach a task or challenge will mean better prompts, which means more helpful output.
- Communication: What makes an LLM unique is the way in which we communicate with it. Whether it’s to carry out research or to create copy, using chatbots in your work requires strong communication skills.
- Critical thinking: This is going to be useful for those times that chatbots get it wrong. As I said earlier, there will be errors in their research, so it’s up to us humans to decide what’s credible and what requires a little extra digging.
- Language: Understanding the nuances in the way that you phrase your prompts will allow you improve your wording. Once you can grasp this, it’ll be easier and faster to get the output you need.
- Learning Mindset: To stop yourself from making the same mistakes, you’ll need to remember what worked (and, just as importantly, what didn’t) when using AI tools so that you can save time in future.
Increasing productivity with generative AI: what to remember
Generative AI is already transforming the way we work. If you’re a white collar worker, the chances are that it will have an impact on your industry or role.
Even if you won’t necessarily be replaced by AI, you might be replaced by somebody with superior AI skills. Getting to grips with AI tools now will help you to futureproof your career by making you more productive. If you haven’t already, try using ChatGPT and other models and see how they can help you in your role, following these tips.
President, Hays, Canada
Travis O’Rourke joined Hays 9 years ago after holding various leadership roles elsewhere in the Canadian staffing industry. Travis setup and established Hays’ outsourced talent solutions business and played an integral role in building Hays’ temporary and contract divisions throughout Canada. Initially joining Hays with a deep background in Technology, he holds extensive cross functional knowledge to provide clients with talent solutions in Financial Services, Energy, Mining, Manufacturing, Retail, and the Public Sector.
Travis is the Toronto President of ACSESS (Association of Canadian Search, Employment, & Staffing Services) and sits on the board of directors for the National Association of Canadian Consulting Businesses (NACCB). He has been featured in segments with CBC On the Money, BNN The Open, CTV National and other news outlets. Like Hays, Travis is also passionate about corporate social responsibility and is an avid supporter for Sick Kids Hospital in Toronto.