The smoke and mirrors of AI

Generative AI is taking the business world by storm, not just by creating attention-grabbing headlines, but also by shifting internal priorities and resourcing. Recent research shows 81% of Australian C-suite executives from large businesses see generative AI integration as critical, and more than a third refer to it as a top priority.

However, there is a distinct difference between claiming a technology is a priority and investing in that technology in ways that drive tangible business outcomes. Furthermore, there is too often a misunderstanding of what AI is, with many businesses confusing AI with machine learning. This combination is leading many business leaders to not always ‘walk the talk’ as they get distracted by the hype of AI, rather than its practical capabilities and applications.

The pressure to be at the cutting edge

In reality, outside of large language models (LLMs) like ChatGPT, there are very few business cases for AI that showcase its usefulness in achieving business outcomes. Despite this, there is an ongoing pressure among business and technology leaders to be seen to be adopting or at least investing in AI, with the aim of portraying to investors, staff, partners, and customers that they are making a concerted effort to futureproof their business against the next competitive threat.

For many businesses, these wasted resources and investments are the result of a classic case of being distracted by the latest shiny new toy, when those same resources and investments could go towards other tools to deliver the desired results in a shorter timeframe.

Businesses need to get real-time data right

Real-time data and analysis are the first, if not biggest, barriers preventing AI success. Without having these solid fundamentals in place, AI has little practical value and, consequently, it is here that businesses should be redirecting any efforts ahead of attempts to implement and make the most of AI.

Accessing the right data to achieve the right outcome can still be extraordinarily difficult and taking the next steps in making that data actionable requires a broader awareness of the new technologies and platforms out there that can help, as well as a fundamental understanding of the journey needed to deliver on it (and AI’s) full potential. If executives fail to invest in and prioritise this endeavour, the result will be more than just disappointed and confused stakeholders — the impact on a business’s bottom line could be catastrophic if they fail to set up their teams for success compared to a competitor who does.

One of the core differences between AI and real-time data is that the acquisition and use of real-time data is actually achievable today, whereas AI is mostly yet to prove itself valuable in optimising business outcomes. Businesses that can get good, reliable, free-flowing, and real-time data will be the most competitive because they will have the best chances of streamlining the way they work and their overall operations.

Shift AI discussions from top-down to bottom-up

A significant driver of the ‘smoke and mirrors’ effect of AI on the business sector, has been the fact that discussions around AI are often driven from the top down. In many cases, it is a member of the C-suite who wants to prioritise AI, which leads to a domino effect of new hires, investments, and projects. While this is an effective way to get AI on the agenda, this is also how AI can become more lip service than an effective part of the business strategy.

Businesses should be turning to people at the coalface for ideas, approaches, and priorities when it comes to AI. Listen to employees working within the organisation to discover where decision-making support and predictive insights would be useful; talk to customers to discover where there are pain points; and hear from prospects about what competitors are offering that is putting your business at a disadvantage. Leverage those findings to develop practical — initially small-scale and targeted — AI applications in a way that democratises access to, and benefits from, access to your real-time data.

Rather than leaving AI to continue to be a long-term pipe dream for the C-suite, transform real-time data into something tangible and usable, and that delivers actionable insights that anyone within the business can use to improve efficiency, the way they work, develop more effective processes or innovate in ways that the business has not yet been able to accommodate.

As business and technology leaders continue to be surrounded by rhetoric and excitement about AI, savvy leaders will recognise the greater opportunity lies in prioritising how the organisation collects, analyses, and capitalises on real-time data. This is one of the few foolproof ways organisations can make impactful preparations today for the AI future that is currently beyond the grasp of most businesses.

Top image credit: iStock.com/Thanadon Naksanee