AI stands for artificial intelligence – the simulation of human intelligence by blending computer science, software programming and large-scale data sets to perform functions without human interference. When realised as intended, AI can automate many business operations, like supply chain management, construction and manufacturing, as well as how businesses source and acquire goods and products…
How does it apply to procurement?
Modern procurement encompasses many factors. Not only is it a collaborative effort between many departments –like external suppliers and management teams – it's also forward-thinking, balancing forecasted challenges and seeking to solve potential problems ahead of time.
Because data forms the backbone of any strategic procurement plan, these insights can be used in conjunction with modern computing to automate the process more efficiently and with minimal human oversight.
When integrated into a considered procurement plan, AI can evaluate data around potential products and trading partners – like spend analysis, contract information and manufacturing times –to find the best opportunities and flag any complications.
What are the benefits of using AI in procurement?
There are many advantages to using AI in the procurement process compared with traditional manual methods.
The advantages of embedding AI in your procurement process include:
AI supplier discovery tools transform time-consuming manual tasks – like unit price comparisons and ROI calculations between vendors – to streamline the vendor selection process. This means they can be completed much quicker, allowing procurement professionals to focus on high-value tasks.
Human error can play a role in inefficiencies or oversights when comparing vendors or suppliers. With the right algorithms, AI can tabulate more data than humans in a given timeframe and with greater precision and accuracy.
After the initial purchase price of AI systems, over time, businesses will save money compared with procurement staff overseeing time-consuming manual tasks.Instead, staff are free to focus on higher-value tasks like managing key partner communications.
How can AI be integrated into procurement processes?
The procurement process can be broken down into four key steps:
· Requesting quotes from vendors, manufacturers, or suppliers.
· Working out contracts, pricing and deliverables with the supplier.
· Completing the purchase orders.
· Establishing and managing the supply chains.
AI can be integrated into almost all aspects of procurement – streamlining the evaluation process by managing costs, flagging potential issues and finding the most efficient, scalable suppliers much quicker and more efficiently than when done manually.
When the supplier has been confirmed and the supply chain created, AI tools can improve accuracy, efficiency and safety in supply chain processes – forecasting demand, solving warehouse issues and flagging unforeseen changes.
This saves on costs, reduces stress on supply chain and logistics providers and ensures that goods are procured in as timely a manner as possible – strengthening customer service potential.
What are the potential risks or limitations of using AI in procurement?
Unfortunately, AI can also present potential disadvantages – particularly for small to medium-sized businesses.
Some of the disadvantages of AI in procurement include:
High implementation cost
AI technology is inherently expensive, making it nearly inaccessible for small or medium-sized businesses. In addition to the high setup costs, AI specialists must be brought in to oversee the transition and guarantee seamless operation, further adding to the initial setup costs.
Unlike humans – who can provide a rational explanation for their decisions– AI can drive decisions without justification. It's notoriously difficult to trace the path of logic a machine or AI software follows to inform its recommendations, which can cause confusion amongst procurement staff and upper management.
Increased potential for disruption
Those that attempt to cut corners and pursue an AI-led procurement strategy without a thorough deployment plan face disruption throughout the process and within the wider supply chain.
Redundancies are an unfortunate outcome of widespread automation. A move towards autonomous procurement means those working in the sector must be trained to work alongside AI or risk being phased out.
How can AI be used to improve supplier selection and management?
Typically, AI can take internal data and information from vendors and use it to make key procurement decisions.
As well as analysing data, natural language processing (NLP) algorithms can scrape contracts and supplier descriptions to establish the needs of suppliers and businesses and identify the best match in the negotiating stages.
This can cut down the process of finding suppliers from months to days and even hours – making it attractive for many retailers and businesses.
What are some examples of AI in procurement?
AI can be broken down by type and style and used for different purposes in procurement:
Artiﬁcial Intelligence (AI)
Software and algorithms that use data to inform decisions, make recommendations and execute functions with minimal human intervention. Can be used to make the entire source-to-contract process more efficient, from reviewing bids to managing purchase orders.
Machine Learning (ML)
Software and algorithms that highlight patterns and use this to inform decisions and make long-term projections. For example, identifying and consolidating all data from a single provider for ease of access and decision-making.
Natural Language Processing (NLP)
Algorithms that can read, interpret and replicate human language. This type of AI is typically used to read contracts and decipher meanings that can be helpful in procurement negotiations.
Robotic Process Automation (RPA)
Algorithms that carry out more menial, simple functions quickly and accurately – such as monitoring inventory levels and creating purchase orders.
How can companies ensure that AI is used ethically and transparently in procurement?
Because AI solutions run on data – and are programmed to find the most efficient solutions – social, ethical and environmental concerns can take a backseat to the most cost-effective solutions.
AI systems need compassion built into them to find the most ethical solutions. One of the ways businesses can do this is through subtle data manipulation to achieve the desired outcomes. For example, data surrounding carbon emissions and ethics protocols can be added as an extra factor that AI must consider in its decision-making.
NLP systems can also be adjusted to focus more on specific ethical language use in contracts – helping to combatAI's natural hyper-focus on efficiency.
What does the future of procurement look like?
The future of procurement is set to be shaped by AI integration – driving time and cost savings for businesses. The focus of future procurement will include:
Future procurement will hone in on the needs and wants of the customers. As customer requirements change – like demands for more informational transparency on the products – the procurement process will spend more time finding out what their customers need and scouting vendors who can best supply products for them as opposed to what's the cheapest. The ability of AI to support the analysis of large data sets will allow these considerations to be integrated into the bid invite and RFx processes with minimal disruption and time investment.
Ethical and sustainable procurement
As corporate social and environmental responsibility grows, modern procurement will have sustainability at the forefront. From getting environmental commitments down in writing to scoping potential vendors’ emission-cutting activity on the ground, the desire from businesses and customers to go green incentivises a move towards eco-friendly procurement. The application of AI and NLP technology will allow businesses to increase their requirements at the source-to-contract stage without delaying projects or adding to manual workloads.
The role of third parties in procurement
Third-party analysts may be better positioned to match potential vendors to businesses and vice versa. This may be advantageous for smaller companies that can pay a smaller fee to outsource their procurement, levelling the playing field. This may also give smaller businesses access to the power of AI where they would otherwise be unable to fund the technology in-house.
Frequently Asked Questions (FAQs)
How do you automate procurement?
Automating the procurement process can be a challenge. However, there are a few things businesses can do to speed up the process and ensure that the integration process runs smoothly. When automating your procurement process, it's crucial to:
Outline your own processes
Before considering AI integration, businesses must first analyse and audit their unique procurement process. This uncovers what areas of their procurement operations can be fully automated or where AI can assist to boost efficiency.
Work out your budget allocation
AI is expensive and, sometimes, fully automated processes do not represent a cost-effective option. Instead, identifying the key areas in which AI would provide the most value relative to cost can see businesses reap the greatest rewards.
Select the right software to do the job
It's vital to have the right software for the desired function and not to waste time and money implementing AI features just for the sake of it. For example, if a business' procurement audit reveals that they are overburdened with menial tasks – like price gathering and reviewing vendor quotes – they should hone their resources towards RPA systems rather than implementing a generic AI solution that doesn't tackle their specific issue.
Build the automation workflows
Any AI solutions must work with your company's existing infrastructure and any rules and regulations they must abide by. AI technology must be programmed with business rules and logic at the forefront of any decision-making to guarantee compliance on all levels.
Quantify your results to measure improvement
To ensure your AI implementation strategy has the desired effect – like streamlining menial tasks, slicing costs and speeding up the procurement process – companies must measure it against specific metrics to gauge success. For example, many prominent businesses use metrics like procurement cycle time(PCT), supplier lead time (SLT), product quality and price to measure the success of an AI-selected vendor.
Can AI replace procurement?
AI is an effective tool, but it can't do everything yet.
Because AI operates using large data sets, human supervision in the form of AI specialists is still needed to fill in the gaps in knowledge around more subjective data points, like vendor choice and contract details.
While AI is supporting in making the procurement process more efficient – by automating manual tasks and avoiding human error – it will never be able to fully own the process and will always require human intervention, for example, in reviewing results and performing quality checks.
Which companies use AI in supply chain management?
Many well-known companies implement AI systems to bolster efficiency throughout expansive global supply chains.
For example, Apple employs machine learning AI to sort products for shipping within its supply chains.Over time, these machines get more efficient at processing products for distribution, while separate AI systems have improved demand forecasting and planning when manufacturing new products for different markets.
Amazon also incorporates AI and machine learning to manage its supply chain network. Predicting the popularity of products and ensuring inventory levels match demand is vital to Amazon's business model.
How can DeepStream help?
DeepStream simplifies the source-to-contract process – giving your procurement managers more time to spend on high-value tasks.