What’s next for generative AI in enterprises?

5 Jan 2024

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Thor Olof Philogène, the CEO of AI-powered enterprise insights platform Stravito, explains why he thinks the next wave of generative AI will lead to greater workplace innovation.

With its ability to integrate large catalogues of existing content to find unique connections and quickly answer questions with natural language responses, generative artificial intelligence (AI) has already proved enormously beneficial to knowledge workers and companies, across a range of verticals.

Just as computers and the internet delivered vast efficiency improvements for documentation, information reproduction, communications and data gathering, generative AI can help improve productivity and accelerate decision-making with its unprecedented analytical power.

As technology advances and new opportunities are created, it’s undeniable that some tasks traditionally performed by knowledge workers will be automated. But this doesn’t mean the role of humans will be replaced, instead it will be elevated. Generative AI is already beginning to emphasise the importance of specific hard and soft skills for the workforce that only humans can have.

Changing the search experience

Generative AI is currently enhancing the abilities of knowledge workers to rapidly explore existing content and data, inspiring creativity through novel perspectives and connections based on deep data analysis, and eliciting a more engaging user experience with a personalised approach.

In more general terms, the technology is helping workers find answers and form conclusions that would be extremely difficult to unearth if the process relied on individual workers researching, reading, understanding and identifying connections among hundreds or thousands of individual data sources.

The greatest effect AI has had on insights work so far is changing the search experience into a conversational task where workers can ask a question and receive complex, full-sentence answers that combine data and input from multiple sources. With natural language AI capabilities, workers no longer have to wonder which specific search terms will return relevant documents or sift through vast numbers of reports, instead they can simply ask a specific question such as ‘What are the trends in packaging for non-dairy milk?’ and get back a succinct answer based on multiple referenceable sources.

Soft and hard skills will enhance AI

While extremely beneficial for work productivity, some situations involving generative AI lack clear data or involve ethical or emotional nuances. Human soft skills like emotional intelligence and empathy are essential for navigating these challenges, understanding the feelings and motivations of others, and making ethical choices. AI can’t independently make ethical decisions, so it’s up to humans to program, oversee and ensure the ethical use of AI.

Currently, generative AI can provide comprehensive data and easy-to-understand insights to assist in decision-making, but it can’t interpret the broader business landscape or market dynamics, nor can it consider or compile long-term strategic plans. Planning will remain a human endeavour that relies on experience, intuition and knowledge of internal and external pressures and opportunities.

Human hard skills such as prompt-writing, fact-checking and category expertise will continue to form a critical part of workflows as well, as long as AI remains prone to the infamous hallucinations associated with some tools. It’s more important than ever to verify and validate information, emphasising the importance of this skill to maintain credibility and reliability as content creation accelerates.

Workers who can quickly craft effective prompts are also essential to ensure relevant and coherent responses, with even minor differences in prompts returning vastly different results. The most used generative AI systems tend to lack deep category-specific knowledge required to interpret industry jargon, so they can make mistakes or leave out important context. That’s why human experts who possess in-depth understanding of a particular field are vital for guiding the AI and interpreting search results to consistently deliver contextually relevant decisions.

The future of human-AI collaboration

Beyond insights, generative AI search will be integrated into all aspects of business in the years to come, but its use won’t stop there. Just as technological advancement has made the idea of a pure internet company or mobile company obsolete, we don’t expect to see generative AI companies. Instead, the technology will function more like electricity, powering all kinds of use cases and streamlining workflows and tasks. It’s even been referred to as a ‘first-draft machine’ for its ability to quickly summarise notes, bullet points, memos and other documents into easily digestible formats that can be edited and perfected by a human, eliminating some of the steps and enabling faster completion.

However, even with all its power and speed, generative AI insights services are not eliminating the roles of workers, they are simply changing them. Data is never perfect and the technology cannot consider or evaluate the ‘why’ of an answer to determine the best course of action. Limits to data quality and quantity often necessitate creativity on the part of the worker who is crafting AI prompts, and once results are delivered, the workers’ experience and knowledge of peripheral concerns plays a vital role in deciding how to best leverage the insights.

The future of business will be laden with exciting new tools and technologies, with AI increasingly branching into more disciplines and industries where it can help improve decisions and overall results. With thoughtful implementation, these tools will eliminate simpler tasks and allow workers to focus on creativity and ideation that drives innovation and growth.

By Thor Olof Philogène

Thor Olof Philogène is the CEO and founder of Stravito, an AI-powered enterprise insights platform that allows employees at Fortune 2000 organisations to store, discover, share and integrate consumer insights, in seconds. Prior to starting Stravito, he was chief revenue officer and VP for growth at fintech company iZettle (now Zettle by Paypal). He holds an MSc in Business Administration from Stockholm School of Economics.

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