More than a third of companies have adopted some form of AI in the past year, according to an MHR Analytics poll.
The poll revealed 38 per cent of companies have made the leap to AI or machine learning by adding the technology to their analytics approach in the past 12 months.
Almost a fifth (19 per cent) of the 500 professionals polled on Twitter said their company had made ‘significant’ progress with adopting AI, and a further 19 per cent said their company had ‘steadily’ been adding the technology to their analytics strategy.
Nick Felton, MHR Analytics’ SVP, commented,
We are now seeing a clear shift in focus in the way companies operate their analytics, with AI capabilities like NLP (natural language processing), machine learning and conversational analytics becoming a reality.
With widespread awareness about advances in AI, we wanted to explore current levels of actual uptake as we approach the next decade. It’s unsurprising that a significant number of organisations have this year stepped up and begun to invest in AI or machine learning of some kind.
Businesses are now well aware of the need to adopt this technology and the advantages it can bring to them, such as increased efficiency, revenue growth, customer experience and overall reductions in operational costs, not to mention the control and stability it can offer in an unpredictable business climate. More and more technology leaders and analytics teams are not waiting any longer to invest in AI as they know that these technologies can empower them to succeed.
Our poll also showed that a large proportion – 62 per cent – are still not investing in AI at all which mirrors what we have heard from a number of our 750 customers over the past year. Despite awareness of the benefits, the majority of organisations still perceive challenges to embarking on the data journey, from ‘operational’ or manual-based analytics, to automated analytics. We launched our data maturity quiz earlier this year, as a diagnostic tool to help companies understand how to overcome those challenges and take the first simple steps to implementing more sophisticated and effective analytics systems.
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