Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

The Practical Applications of AI in Workplace

ChatGPT has become the latest buzzword in the tech sphere, with much being written about this new tool and its potential impact on different industries, from education and science to art and design. But what are the real implications for the workplace, and how can AI-driven tools truly impact the future of work?

As Winston Churchill once said, we are reaching “the end of the beginning”, when it comes to AI in workplace.

I came to this conclusion after experimenting with OpenAI’s “playground” a few weeks before they launched ChatGPT last year. I wanted to see how far things had come along the dimension of what’s practical and what I found suggested that AI had finally crossed the tipping point from the lab into our daily work lives.

Recommended: Snapchat Is Back: Introduces Its Very Own Chatbot, My AI, Powered by ChatGPT

I began by using the algorithm to categorize research verbatims into themes and to provide a summary with examples. A task that might take a junior analyst a couple of hours to do, was completed instantly, and the output was usable without any significant edits. My colleague entered a few simple bullet points and was provided the full prose for a conference invitation. These were not tasks that could yet replace whole types of jobs, but ones that could immediately reduce the volume of work.

Related Posts
1 of 16,174

By using natural language inputs, any request framed in a conversational sentence or two can be tackled by the algorithm. Now the benefits of AI are accessible to everyone and we are just a few entrepreneurial applications away from reducing the work that bogs down enterprises and demotivates staff. Just think how much time we waste editing spreadsheets and presentations alone.

So what practical applications of AI in the workplace can you try today?

  1. Generate a first draft. There are always documents we struggle to get around to writing, so why not use this experiment to tackle one of those? Enter a few bullets of content and some simple instructions and see what it comes back with. And the best part – if you don’t like what you get, you can hit refresh and get another take on it.
  2. Make something better. AI may be good at first drafts, but it excels at doing the final clean-up of a document. This goes beyond just fixing the grammar; it can help you say the same thing in half the words. Turn paragraphs into bullets, bullets into long-form, change the first-person to third, the list goes on.
  3. Summarize a meeting. Before recordings and transcriptions on Teams or Zoom, managers used to get helpful one-page summaries of group discussions. But instead of slogging through the transcript of a meeting you have missed, let AI summarize it for you.
  4. Create a value proposition. AI can turn technical product specs into a clear description of what something does – or even a compelling new customer-facing value proposition statement.
  5. Empower your team. Let’s be clear – I would encourage everyone to try it for themselves. However, if you simply don’t have the time, you can ask one of your team to experiment for you. In less than an afternoon they should be able to come up with a number of time-saving ideas for reducing tedious tasks that are hampering productivity.

While we are still a long way off from where this is all going, we have to acknowledge that things will now move at a much faster pace. We must accept AI as a co-worker who is here to stay – a wakeup call for us humans to up our game.

Top Post: Explainable AI: 5 Popular Frameworks To Explain Your Models

The truth is, too much “dumb” work has been sapping the energy and potential of our organizations for too long. Now that the means exist to draw a clearer line between work that must be done by humans and work that can be done by technology, we should all seize the moment.

Comments are closed.