A worldwide study of supply chain, procurement and finance business leaders has found that 55% of organisations are set to make a major investment in artificial intelligence (AI) over the next two years.
A further 25% also plan to make a minor investment in AI to determine its potential ROI over the next two years.
The research, conducted by Forrester Consulting and commissioned by Ivalua, revealed that finance, supply chain and procurement business leaders believe that one of the biggest challenges to adopting AI is the poor quality of enterprise data.
Almost two-thirds of respondents (59%) said that poor data quality will make it impossible for AI to make accurate and informed decisions, undermining their ability to get value from any AI investment.
“There is clearly a huge appetite for AI and this will only increase as more relevant applications and success stories come to light,” comments David Khuat-Duy, Corporate CEO of Ivalua.
“But when investing in AI, it’s important that organisations address challenges that will otherwise limit value. Driving accurate insights from AI is reliant on having a solid data foundation from which to work, and the findings show that this remains a significant obstacle for most organisations.
“Success requires organisations to simultaneously address enterprise data problems when investing in AI.”
Improving the calibre of data is no easy task, with respondents detailing that their inability to access data (44%), a lack of normalisation between data sets (43%) and inaccurate data (41%) as their biggest challenges to improving overall quality. In addition, 36% cited that information overload and lack of internal skills makes it difficult to make sense of data.
In addition to data challenges, 44% of respondents said they do not have the support of C-level executives regarding AI innovation.
They also claim that they aren’t currently able to get full value from AI due to the immaturity of applications, with 62% citing this as a problem, suggesting AI vendor marketing is far more advanced than capabilities. There is also uncertainty regarding how to apply AI to certain use cases (47%).
In terms of the practical uses of AI, the study details that respondents believe it can have the most impact in alerting the enterprise and suppliers to supply chain disruption (44%), recognising and flagging supplier compliance issues (39%), and quickly identifying instances of fraud (37%).
In addition, respondents think that AI adoption will lead to greater automation of menial tasks, making them actionable in minutes or seconds, instead of hours or days.
Two of the biggest areas flagged by respondents as having the greatest potential for automation is invoice processing (51%) and approval of proposed purchases (35%).