An article for business leaders, intelligence professionals, and decision-makers in enterprise Tech companies navigating the challenges of AI integration.

Despite a high level of confidence in AI’s capabilities, daily usage remains low within enterprise Tech organisations. This article will explore the barriers to wider adoption, including concerns about misinformation, bias, and the challenges of updating established processes. It will also highlight the importance of transparency and leadership in fostering a culture that effectively integrates AI into decision-making and market intelligence.

The AI paradox: trusted but underused by enterprise tech firms

According to AMPLYFI’s latest research, over three quarters of respondents (97%) deem AI to be trustworthy, yet only 6% use an AI tool to provide market intelligence every day, with most (38%) only using it 2-3 days a week. In short, this tech is being underused. 

The rise of AI is one of the most debated topics in modern business, and to say there are mixed feelings towards this tech is an understatement. In our industry survey of 1,000 intelligence professionals, we assessed the latest opinions amongst different industries, and enterprise technology professionals stood out as being the most conflicted: they express high trust in AI capabilities yet remain low in actual usage. 

So why isn’t AI being more widely implemented across the sector?

This could ultimately be due to many possible reasons, including teams being unsure of how to apply AI technologies to their workflows and projects. An uncertainty around replacing existing (long used) processes is also often the barrier to change, so even when there is appetite to embrace the new, this is all too often outweighed by disrupting the old (and established).

The public view of AI

A massive 88% believe that popular generative AI models like ChatGPT are actually eroding people’s trust in the tech.

Witnessing how AI can benefit you in your role will undoubtedly sway your opinion. The problem is, so many people have made ChatGPT and the likes – with all their limitations – synonymous with AI in general. But these models do not reflect the full capability of AI – which the enterprise tech sector is clearly aware of, hence the high level of trust.

Enterprise tech professionals recognise the specific benefits of AI, such as:

• Fast data analysis (37%)
• Identifying market opportunities (36%)
• Improved accuracy of research (34%)

One of the primary barriers to adoption is trust, as consumer LLMs e.g. GPT can create false information, hallucinations and generate low quality repetitive content.

However, when specialist enterprise AI tools (not just generalists like GPT for every task), AI offers several benefits. For example, one of the inherent issues when validating content across market intelligence is researcher bias – but with AI, that’s no longer a concern. Here are the different types of biases that impact perceived trust of content that AI helps overcome:

• Confirmation bias – tendency to seek out, interpret, favour and remember information in a way that confirms or supports one’s pre-existing beliefs or values. In market intelligence, it can lead to skewed data interpretation and potentially flawed strategic decisions.
• Primacy bias – tendency to remember and give more importance to the first pieces of information we encounter. This is linked to how information is stored in our long-term memory, making the initial items in a series more memorable than those that follow.
• Recency bias – tendency to prioritise and better remember the most recent information or experiences. This is associated with the short-term memory’s influence on our perceptions, giving undue weight to the latest events or data over historical ones. i.e. confirmation, primacy and recency.

Discover the data behind our insights

How to embrace AI

Trust is key to unlocking the full potential of AI in market intelligence. Despite believing that popular generative AI tools like ChatGPT are eroding the public’s trust, enterprise tech professionals are quick to promote AI’s application in business, and so a lack of appetite clearly isn’t the barrier to implementation.

To improve broader opinions of AI, respondents have named transparency as being paramount, with 67% saying clear evidence of AI’s ability to deliver accurate results will only help improve trust in the technology’s insights. Furthermore, a third of professionals (33%) believe clear AI policies and guidelines – potentially through advancements in regulation – are crucial.

Leadership also plays a vital role. By advocating for and investing in AI technologies that align with business goals and alleviates inefficiencies across the team, leaders can foster a more widespread culture that embraces AI.

Trustworthy AI’s ability to improve access to validated, reliable information – with removing researcher bias – is particularly valuable for market intelligence teams across all sectors. As AI usage in this function continues to increase, we can expect a rise in AI fluency among tech leaders and a growing reliance on AI for strategic business decisions – with trust as the foundation.