Artificial intelligence (AI) and so-called “cognitive analytics” hold considerable potential for supply chain disciplines such as procurement. After all, as Dr. Alan Holland, founder and CEO of Keelvar, wrote on Spend Matters earlier this year, AI is better than humans at detecting patterns in large data sets, e.g., spend analytics; and strategic reasoning in large and complex decision spaces, e.g., strategic sourcing.


Indeed, basic machine learning technology is already used by some procurement applications in areas such as spend analytics and contract analytics, Rob van der Meulen, UK PR Manager for Gartner, wrote on a Gartner blog. This is mostly limited to automating the processes of collecting, cleaning, classifying and analyzing expenditure data in an organization to identify savings or paths to greater efficiency, however procurement technology vendors are creating cognitive procurement advisors (CPAs) and virtual personal assistants (VPAs) which use natural-language processing (NLP) and natural-language generation to further increase automation and efficiency, he wrote.


“A procurement VPA can improve the end-user experience of traditional procurement tools and increase spend under management by guiding people to the correct purchasing tool,” Magnus Bergfors, research director at Gartner, says in the blog post. “A CPA can provide summaries, recommendations and advice in everything from supplier assessments and performance management, to risk management and compliance.”


It was somewhat expected then when SAP Ariba announced plans for an AI-powered enterprise digital procurement bot which will allow users of its cloud-based applications to manage key tasks. It reportedly will interact with the users wherever they are—from web applications or any communication channel.


“Through its bot, the company plans to enable buyers and suppliers to converse with their SAP Ariba applications much as they would Siri or Alexa,” the company said in a statement. “Leveraging machine learning, the bot will be able to train and learn about a user’s preferences and a company’s policies and procedures, and guide actions in-line with them to reduce errors and speed processing.”


The competitive advantage of using AI-based tools springs from several factors. First, procurement managers become empowered to take fast, proactive measures despite the ever-changing dynamics of inbound supply, Rajesh Kalidindi, CEO & Founder, LevaData, wrote on EBN online last month. AI-based insights provide timely business intelligence to these same managers on emerging risks and opportunities. Furthermore, he wrote, with advanced analytics at their disposal, supply chain managers can transform their sourcing negotiations from annual or discrete events into an ongoing process. These abilities drive up incremental gross profit margins, and also provide optics into potential revenue savings, he continued.


With those comments in mind in mind, it wasn’t surprising when LevaData launched its flagship product, Leva, which the company calls “an AI advisor for strategic sourcing and procurement.” As the company explains, Leva is designed to “provide supply chain and procurement professionals with maximum purchasing leverage” by drawing on a proprietary ontology of more than 40 negotiation levers to recommend the most effective lever and its use, in the right context and sequence, to “dramatically” improve negotiation strategy and outcomes.


Built on the company’s Cognitive Sourcing Platform, Leva also enables a “cognitive sourcing cycle” which “senses” opportunities and risk, and then offers prioritized actions, ranked by financial impact and time horizon, says Kalidindi. That’s possible, he says, because Leva “ingests hundreds of thousands of sources of insights, including changes to enterprise spend and forecast information, as well as market intelligence, benchmarking, and more than 5,000 news sources, to deliver actionable insights.”


What are your thoughts on the use of AI for specific roles in the supply chain? Secondly, what impact do you think use of AI would have on the ability to address complex sourcing issues?