5 Uncommon Yet Fascinating Ways AI Can Supercharge Business Productivity AI-powered productivity gains can be endless if business leaders know where to look.
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Artificial intelligence (AI) is arguably here to stay, following its skyrocketing popularity over the course of 2023. However, the technology's longer-term impact on the workforce is less understood. According to a report published by the European Parliament, by 2025, AI has the potential to boost productivity across the continent by 11%.
Still, we're only in the nascent period of AI development: Data looking at technology's historical impact on productivity is less promising. The UK's National Institute of Economic and Social Research found a 1.8% drop in the rate of productivity growth between 2008 and 2020, compared to the period spanning 1974 to 2008.
The natural next question to ask is: How can founders and business leaders ensure they reverse this trend with the help of AI during a tricky economic period?
Realising these promises of productivity is not a simple case of "plug and play" for business decision-makers. Without fully understanding and harnessing the full range of use cases it unlocks, their chances of making the most of its potential are slim.
AI boasts a huge range of business use cases, from automating presentations and reports with ChatGPT to sophisticated functions like converting legacy code and debugging for software developers. Here's a look at five new, unusual, and fascinating applications that exist in places you wouldn't necessarily expect to find them, empowering founders and their businesses to supercharge productivity.
1. AI-powered sentiment analysis for employee wellbeing and efficiency.
As a less well-known use case, AI technology can be used in employee surveys to help founders gauge how supported, engaged and motivated their workforce feels. This is crucial when you consider the growing importance workers are placing on having a healthy work environment alongside straightforward professional achievement.
Externally, it can also be used to identify and extract subjective information from a piece of text (such as tweets, emails, or articles) to determine overall sentiment and highlight specific opinions and emotions in content. This is ideal for product reviews and competitor analysis, as it increases the overall efficiency of day-to-day work for businesses across industries.
2. Chatbots to streamline internal and external comms.
Another uncommon example of AI boosting productivity comes in the form of companies creating chat-like interfaces that act as so-called "knowledge base assistants." Firms like Slite are increasingly using AI to create a so-called "single source of truth", boosting productivity for growing teams by providing an instant outlet for staff to access trusted company information.
Founders and startups should be wary of chatbots' uses geared toward generating interest for the sake of it or for general purposes like increasing user retention. Instead, another lesser-known use case of chatbots that is rife with productivity potential involves their conversational ability – generative AI tools like ChatGPT could be used to 'test drive' proposals for clients or role-play the most likely response to suggestions.
3. Transcription: Mix and match for maximum effect.
Free real-time AI transcription tools are unlocking resources across teams for higher-level, strategic tasks and thinking by automating everyday administrative tasks. For example, Opus uses AI to shorten and transcribe video clips for companies to use in their marketing channels.
But, with many AI transcription tools now claiming an accuracy rate of more than 90%, founders can achieve far greater productivity than they currently are by combining their applications with other use cases. For example, pairing super-fast and accurate transcription with sentiment analysis following a simple weekly catch-up call could provide a clearer picture of crucial metrics like client or customer satisfaction, team morale, and enthusiasm towards specific projects.
This "mix and match" approach to using AI boosts productivity by improving leaders' understanding of their workforce, and illustrates the importance of pairing AI's power with uniquely human creative thinking and problem-solving.
4. Enhanced data quality and time savings.
Leveraging AI for data analysis and summarisation enables a range of productivity-boosting functionality including tagging customer support tickets, filtering items to troubleshoot, or incorporating tags for new product features.
A more novel example could involve using AI-based anomaly detection to label high-priority documents such as client-facing activity trackers. This helps to ensure enough time and attention is allocated in the right places across the organisation and protect potentially sensitive data.
One specific use case I've encountered involves e-commerce firms using AI to detect mismatches between the expected delivery price charged by carriers and the actual price. More broadly, using AI tools in spreadsheets can also quickly summarise and condense data into key takeaways to further save time for senior decision makers.
5. AI-powered translation as a window to new business and talent.
Naturally, all the productivity in the world is of no use if companies that rely on customer acquisition and retention can't bring in and keep valued business. In today's interconnected, global society, it's unsurprising to hear that over a quarter (29%) of businesses have lost customers for an inability to provide multilingual support.
Beyond keeping existing customers happy, using AI-powered translation also helps companies tap into new markets and unlocks a far wider pool of new potential business. Most importantly, AI translation can democratise recruitment and talent acquisition by allowing professionals with the right skills to apply for and securing roles where language isn't a key factor in their performance.
AI is the tip of the productivity iceberg.
It's difficult to overstate the range and diversity of use cases that AI presents for businesses, but this is no guarantee that the technology can increase productivity on its own. A great first step for founders is to prioritise fully understanding where it can be harnessed for maximum benefit, rather than implemented for its own sake.
AI-powered productivity gains can be endless if business leaders know where to look. By treating it as the tip of the productivity iceberg rather than a magic pill, and approaching its possible use cases with an open and curious mind, they can give themselves the best possible chance of fully capitalising on its potential.
