What is Artificial Intelligence?
The term ‘Artificial Intelligence’ was first coined in 1956 at a computer science conference in Dartmouth. Put simply, it is the branch of computer science concerned with simulating human-like intelligence in machines. Whenever a computer performs a set of tasks based on some preset rules or conditions known as algorithms, the emergent behavior is called artificial intelligence (AI). For example, AI-enabled machines can detect hand movements, manipulate objects spatially, recognize facial features, and more. It is an endeavor to develop intelligent systems that can closely mimic human intellectual processes, like the ability to reason, learn from past experiences, generalize, and find hidden meanings.
AI has a wide variety of applications across various industries – e-commerce, automotive, healthcare, B2B software, and more. But perhaps the biggest paradigm shift brought about by AI is in the manufacturing and sourcing industry. Let us take a deeper look:
Artificial intelligence sourcing
A typical sourcing process contains the following variables – supplier selection, supply chain, customs navigation, government regulation, vendor management, payments tracking, and more. Needless to say, these processes are extremely cumbersome and time-consuming, requiring enormous amounts of human coordination. Any slip-ups in these mechanical routines can mean hours of redundant rework. If material is sourced from overseas, the complexity goes up by another order of magnitude.
AI solutions can simplify these processes manifold, leveraging big data and analytics to breeze through the above mundane functions. AI-driven data analytics can be categorized as follows:
Descriptive: Gives a comprehensive description of business fundamentals, whereby sourcing professionals can access a goldmine of information related to spending profiles, at a fraction of the cost and effort.
Diagnostic: Provides tremendous insight into the root causes of any fluctuations in the total cost of ownership, saving costs considerably.
Predictive: AI can be leveraged to forecast raw material requirements per geography based on customer order volumes. Prescriptive: AI can prescribe a set of options and best-case scenarios during vendor selection, price negotiation, bidding strategies, and more, thus easing the decision-making process significantly.
How AI can help in procurement
Here are the ways AI advances can revolutionize the procurement process:
1. Adding a layer of smartness: According to a study by Ivalua, AI smarts can alert businesses to supply chain breakdowns, identifying and flagging compliance issues, and fraud detection. Gartner reports that AI is also being leveraged in spend and contract analytics, minimizing costs, increasing savings, and boosting efficiency.
2. Automation: Processing invoices and purchases approval are two menial tasks where AI is proposed to have a sizable impact. Such softwares can streamline the management of thousands of invoices by comparing them with PO’s, vendor contracts, or accounting plans and auto-inserting them correctly into the database.
3. Supercharged Profits: The Market Mogul claims that AI technology can slash procurement costs by 15-25% on addressable spend. And the greater the savings, the higher the bottom-line impact.
4. Detecting anomalies: AI can detect and notify businesses about market anomalies like sudden or unexpected swings in the price of a commodity or from a specific supplier. Other applications of AI in procurement are vendor matching, spend categorization, building supplier data profiles, and more.
What are the 3 types of artificial intelligence?
AI is classified along the following parameters – ability to imitate human characteristics, the technology used, real-world applications, and the theory of mind. Based on these parameters, there are 3 types of artificial intelligence:
1. Artificial Narrow Intelligence (ANI): Also referred to as weak AI, this is the only type of AI we have achieved till date. Possessing a narrow range of abilities, it is designed to focus on a single specific task. Examples of ANI include Google Rankbrain, NLP voice assistants (Siri, Google Assistant, Alexa, Cortana), IBM Watson supercomputer, autonomous cars, disease mapping, NSFW content filtering, content recommendation engines (Netflix, Spotify, Amazon), and more.
2. Artificial General Intelligence (AGI): Also known as strong/deep AI, it is a conceptual machine that is indistinguishable from the human brain and its cognitive abilities. It uses the theory of mind framework, to understand complex emotions, desires, beliefs, and thought processes of humans.
3. Artificial Super Intelligence (ASI): A hypothetical AI that is multi-faceted and self-aware. Not only is it better than humans at objective disciplines like maths, science, and logic; it also surpasses humans in arts, decision-making, and emotional relationships. Think Skynet or the hosts from Westworld.
Procurement AI software
Here are some AI software solutions that can automate procurement:
1. Supplier Risk Management: Risk Methods helps you proactively identify, monitor, and mitigate supply chain management risk.
2. Purchasing: Trade shift lets you swiftly screen and sanction purchase orders, using AI.
3. Accounts Payable: Stampli automates invoicing and payment workflows and also detects monetary fraud.
4. Supplier Discovery: Tealbook leverages machine learning to identify, organize, and use supplier data, acquired and enriched from various sources on the Internet.
5. Contracts: Seal Software (acquired by DocuSign) automatically scans and analyzes dense legal contracts to identify prospective loopholes and savings opportunities.