AI: the key to productivity and time-saving in business

Generative AI can save businesses time and money while boosting creativity and productivity, but it’s vital to understand its limitations to maximise its benefits

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Generative artificial intelligence (GAI) has fast become a fixture in the workplace – as well as in headlines warning of defunct human employees and the death of creativity.

The truth, in practice, does not tally with the doom-laden messaging. Instead, as demonstrated by research from Capterra UK, a business software comparison and reviews website, there are clear benefits to using GAI in terms of productivity and timesaving.

GAI has many applications – it is capable of generating original content such as images, videos, music, code, or text, by using deep learning techniques and neural networks to analyse and learn from large datasets. These tools, which include ChatGPT, Bard, and DALL-E, generate content that resembles human creations.

“Our report showed that 96% of employees who use generative AI for work feel that it increases their productivity,” says Eduardo Garcia Rodriguez, analyst, Capterra UK. “This statistic underscored the potential for AI to enhance efficiency and productivity. And, 98% of surveyed respondents – the clear majority – indicate that generative AI is of some, or high, importance to their company. Given the supposed scepticism surrounding AI recently, this shows that there is actually a shift in how businesses might view AI, particularly for innovation and creativity, where we have shown that people see the perks and the benefits of it.”

Garcia Rodriguez highlights the fact that 41% of generative AI users deploy these tools for text editing, with 40% using it for text creation, and analytics and reporting. Perhaps surprisingly, 85% said AI boosts innovation and creative work, with nearly as many reporting that working with generative AI saves their company time (83%) and money (81%).

While the latter findings are in and of themselves significant wins, the fact that generative AI helped improve business performance for 79% of respondents ­– and that it produces content that is better than human efforts (70%), further explains why this revolutionary technology has been rapidly embraced. 

ChatGPT usage

But, despite its versatility and immense potential, concerns abound regarding the lack of regulation of ChatGPT. Garcia Rodriguez reports that employees are uneasy about the responsible usage of this tool, with transparency, security and misinformation identified as key areas of concern.

When it comes to verifying the integrity of ChatGPT’s output, Capterra UK found that 60% of users meticulously review every output when using this tool. This indicates that four out of 10 users do not check their outputs consistently, which Garcia Rodriguez says is “alarming”.

As ChatGPT scrapes information from sources without verifying authenticity or copyright rules and because the tool’s knowledge is mostly limited to information before 2021, along with the technology’s tendency to invent facts – known as hallucinations – there is a risk of plagiarism, inconsistencies, or false information, which can be detrimental if businesses do not notice them.

“Employees are open to using AI but they expect guidelines and oversight,” says Garcia Rodriguez. “In fact, nearly one-third of surveyed ChatGPT users expressed concerns about security and misinformation. But these are things that can be addressed with regulation.”

The UK Government released an AI white paper earlier this year, and, in November 2023, unveiled its new AI Safety Institute, whose mission is to minimise surprise to the UK and humanity from rapid and unexpected advances in AI. The institute will “work towards this by developing the sociotechnical infrastructure needed to understand the risks of advanced AI and enable its governance.”


So, what can responsible businesses do while governments work to formulate official guidance on the use of AI? The answer is: plenty. Being aware of the limitations of ChatGPT is vital. For instance, given the tool’s tendency to hallucinate, employees should avoid asking ChatGPT to name its information sources, as the feedback may be inaccurate due to it not being verified at source. Rather, teams should cross-reference statistics or statements with trusted websites and original references.

Plagiarism is also a risk, as ChatGPT generates text based on training data. Businesses can use plagiarism checkers to compare generated text against a vast database of published material.

Despite its versatility and immense potential, concerns abound regarding the lack of regulation of ChatGPT

Offering employees training on the optimal prompts to use to help fine-tune the content they receive is also beneficial. “It’s important to stress the importance of education,” says Garcia Rodriguez. “Educate employees about the benefits of AI and how it can enhance their work. I think, in general, there’s a curiosity and there are people who might be sceptical about AI, so it would be useful to educate them about how it can be used and how it can help them make their work better.”

As well as this, managers should involve their employees in the generative AI implementation process rather than presenting it without consultation, he recommends. By seeking their input and addressing concerns about the technology via feedback channels, employees will feel more comfortable.

He adds: “The main point is transparency. It is important to communicate the ethical and responsible use of generative AI and to build trust. I think when all this is joined up, employees will feel that it’s a safe tool and [knowledge] can help them with that buy-in.”

Finally, before implementing new software, it’s essential to assess and identify use cases and business goals and determine which can benefit from generative AI, says Garcia Rodriguez.

“Fortunately, to help with this, there are task management tools and project management tools, so businesses can see when an assignment may be improved with generative AI. These can help build use cases to decide whether they need to invest in software.

“Businesses also need to make sure that they have sufficient data for machine learning models in order to deliver the best output. Data preparation is crucial to ensure data quality and protect visibility for these generative AI models. But overall, we need to make sure employees buy into generative AI to use it appropriately.”

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