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AI in Procurement and ‘Autogmentation’ Part 1 — (Procurement) technology is more than automation to replace people


Technological progress has revolutionized the business world, transforming industries and redefining work. For procurement professionals and solution providers, understanding the evolution of technology and its impact is crucial for staying competitive in the ever-changing market. From the early days of mechanization and automation to the digital age, technology has continuously improved efficiency and effectiveness in business operations. It has enabled automation, streamlined processes and enhanced productivity. However, it is essential to recognize that the role of technology is about more than just replacing people with machines. It goes beyond automation to encompass ‘augmentation,’ which involves enhancing human capabilities and decision-making processes.

One of the most significant technological advancements in recent years is Artificial Intelligence (AI).

Visit Spend Matters dedicated ‘Artificial Intelligence in Procurement’ page to learn more.

AI, and, more specifically, Generative AI (GenAI), stands out as a prime example of how technology reshapes work by introducing enhanced ‘collaboration’ between humans and machines (which isn’t just physical robots but also software ‘bots’ that use machine learning to emulate increasing levels of human intelligence). This symbiotic collaboration combines automation and augmented AI for increased decision-making autonomy and job enlargement. It is what we call ‘autogmentation’ (/aw-tog-men-tay-shun/) which is (autogmentation = AUTOmation + auGMENTATION). Although the term is a mouthful, it captures the essence of how ‘augmented intelligence’ (the real way that AI is getting developed and deployed) is getting used to automate next-generation workflows, data (e.g., incorporating natural language and knowledge modeling), analytics, integrations and application development itself.

We’ve covered procurement automation trends, strategies and solutions for decades and have also discussed augmented intelligence within a broader AI and procurement context. In this series, we will delve into the history of technology and its impact on business and procurement. We will explore the evolution from automation to augmentation, highlighting the benefits of efficiency and effectiveness. Additionally, we will provide an in-depth analysis of AI, its history and its unique characteristics that differentiate it from past innovations. Finally, we will focus on GenAI and its potential to simplify processes, increase efficiencies and drive revenue uplift in the procurement industry.

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By understanding these technological advancements and embracing the concept of ‘autogmentation,’ procurement professionals and solution providers can leverage AI, particularly GenAI, to optimize their operations, enhance decision-making outcomes and maintain a competitive edge in the evolving business landscape.

A brief (and simplified) history of technology in the business world

Technology has been a driving force behind business evolution, shaping industries and transforming the way we work. From the early days of mechanization to the digital revolution, businesses have embraced technology to streamline operations, enhance productivity and stay competitive. And, since there is a lot to learn from the technology journey so far, we want to focus on that first.

A timeline of technology in different colors

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Looking at the history of technology in business and, more particularly, at the impact of digital technology, the first notable inventions allowed the digitization (the conversion from analog to digital) of information, enhancing communication between individuals and businesses. For example, the invention of the telegraph in the 1830s allowed companies to communicate over long distances, revolutionizing how they did business — transforming atoms into bits opened the door to the next step: the digitalization of processes, starting with calculators and then computers.

Early computers, such as mainframes, were massive machines that revolutionized data processing. They were much faster and more powerful than previous computers and could be used by multiple users simultaneously. They enabled businesses to handle complex calculations and data storage more efficiently. These machines paved the way for automation, accounting systems and inventory management.

As hardware and miniaturization progressed, mainframe computers lost their place to personal computers. They brought computing power to every individual, fostering a new era of productivity. Software evolved at the same time to simplify the way people were interacting with machines. Word processing, spreadsheets and communication tools became standard.

The next major milestone was the Internet. It connected businesses and consumers globally and allowed them to connect content and systems together through web pages (e.g., via HTML), hyperlinks and web browsers accessing Internet-connected servers. This foundation also automated and democratized commerce and the flow of cash, which in turn allowed companies to reach new markets, customers and suppliers without physical boundaries and limitations.

Mobile and cloud technologies increased flexibility and productivity. Digital technology became ubiquitous, especially with the rise of social media and the emergence of cloud software that could be accessed and rented over the web, i.e., Software-as-a-Service or ‘SaaS.’ This democratization paved the way for digital-first approaches to business models and operations. It also gave birth to the concept of digital transformation, which encompasses all aspects of business regardless of whether they are digital or not, to embrace the massive reach and potential of this technology, enabling the creation of entirely new markets, customers and businesses (people, capabilities, processes, operating models, etc.).

The 2010s were marked by the popularization of ‘big data’ (i.e., massive data sets of various formats generated across the web) and AI. With software developed for this purpose, businesses could further use data analytics to translate valuable insights into behaviors, market trends and ‘outside-in’ data to improve internal operations. AI-powered solutions helped analyze and interpret this data at scale to help humans improve their decision-making processes. Machine learning (ML) algorithms became instrumental in automating even more tasks and optimizing business processes. As AI incrementally permeated lives at home and at work, discussions about its impact on the future of work (and civilization!) and the need for governance emerged and grew over time. Because of its broad utility, the most recent advancement of GenAI made these issues more tangible and concrete for many people in a way that previous AI initiatives hadn’t.

There is much more to say about AI, its history, its impact, etc., and we will cover these elements in greater detail in part 2 of our series before moving on to the specific impact on business and procurement in particular — this way we provide better context for the future. As Albert Einstein once said: “Learn from yesterday, live for today, hope for tomorrow. The important thing is not to stop questioning.” As such, we’ll try to answer as many questions as we can regarding AI and its impact within the procurement technology realm.

Impact on business

A large part of the early history of technology shows that technology’s main impact (and sought-after value) was automation (e.g., operational efficiency). Technology has streamlined processes, automated tasks and reduced manual errors, leading to higher productivity and cost-effectiveness. For example, computers have made it easier to eliminate paperwork (e.g., reducing contract-signing cycle times by over 75% by replacing manual ‘wet ink’ signatures with digital signatures) and software has made it easier to accomplish business-specific tasks. Communication tools, video conferencing and collaboration platforms have facilitated interactions between teams and stakeholders, irrespective of where they are inside and outside the organization.

The same principle applies to decision-making processes (the production of decisions) as expert (rule-based) systems and data analytics have enabled businesses to speed things up (data collection, data analysis, etc.) and use fewer human resources for the same activities and outcomes.

However, technology has had another type of impact on decision-making processes: augmentation. Augmentation, defined generically, is about adding more of something, and in the business realm it’s about digital technology that helps extend worker capacity and capabilities to process, interpret and act upon more information to generate higher value. By being able to crunch more numbers, analyze different possibilities and see correlations that humans can’t, technology has improved the effective outcome of human-led decisions and even built new knowledge.

Then, going beyond incremental improvements of efficiency and effectiveness, technology can make companies go where no company has gone before. Technology allows for (re)invention of old processes. (Re)invention can be in terms of reach (access to new supply/demand markets), customer/supplier/employee experience re-imagining and innovative/disruptive business models challenging traditional industries, e.g., open source models, a firm like Tesla disrupting automotive/energy industries or Uber disrupting the mobility industry. In short, technology lets us do things that were previously impossible.

Impact on procurement

Procurement hasn’t been immune to technology and followed a similar evolution to the one we described for business in general — and it’s something Spend Matters has been covering for almost 20 years!.

Our free-to-use TechMatch tool has been developed to help you match the best procurement technology with your business needs.

Ford’s story about its AP process re-engineering program that reduced headcount by 75% was discussed in Michael Hammer’s legendary HBR article in 1990 (“Reengineering Work: Don’t Automate, Obliterate”) illustrates the journey many organizations took to radically overhaul their processes and then hold the gains of those re-engineered processes through technology automation. It is no wonder that transactional (P2P) processes are where technology penetrated procurement first.

The need and search for automation and efficiency isn’t only something from the 1990s. Over the years, CPOs and CFOs have constantly looked at Source-to-Pay technology to streamline processes and ‘do the same with less’ or ‘do more with the same.’ This is especially true in procurement where money wasted on inefficient transactional purchasing has a massive opportunity cost of investment that is not invested in strategic procurement with a 5-10X ROI based on various industry benchmarks.

For example, the 2023 Deloitte CPO Study (co-authored with Spend Matters) found that leading organizations allocate 56% more time respectively to strategic activities (vs. transactional and operational) than their peers because they “apply more flexible automation tools and methods at roughly twice as much as peers” (and 10 times when considering RPA). The study also revealed that leaders also leverage technology for its augmentation potential as they are three to four times more likely to have fully deployed analytics and visualizations with the difference for AI and cognitive capabilities (16 times!) even more stark.

This evolution of procurement technology is also impacting decision-making activities and not just task automation, which can include repeatable automation of data pipeline workflows for analytics:

Workflow Automation (Efficiency) (Tech. as process administrator)Decision Augmentation (Effectiveness) (Tech. as a SME/colleague/consultant)
  • Code-based rules
  • User-configurable rules
  • Conditional (‘smart’) workflows
  • BPM for cross-app workflow processesing/execution
  • RPA (integration toolkits and bots)
  • B2B integration and self-service
  • Orchestration (above plus advanced planning, monitoring, alerting, etc.)
  • Process mining to analyze and redesign processes for greater efficiency and throughput
  • Focus on data -> info -> Knowledge
    • Tribal knowledge -> Community / collective intelligence ‘Self’-adjusting machines (supervised or unsupervised Machine Learning)
    Spend under management -> Spend under prediction and prescription
    • Prescription and guidance based on ‘sense and predict’Benchmarks and discovery (outside-in)Auto opportunity identification (internal/external)Advanced algorithms for complex problems (e.g., optimization analytics in sourcing bid analytics)
    Reducing information overload and analysis paralysis

And, as noted by Jacopo Colombo, Albachiara Boffelli, Matteo Kalchschmidt and Hervé Legenvre in their research article (“Navigating the socio-technical impacts of purchasing digitalisation: A multiple-case study”) published by the Journal of Purchasing and Supply Management in May 2023: “Efficiency is mainly achieved through automation applications, while effectiveness is achieved through augmentation applications. Data aggregation and automation are mutually supportive; together they facilitate augmentation.”

This relationship between automation and augmentation is what we call ‘autogmentation,’ and it leads to “increased decision-making autonomy and job enlargement.”

So, the history of digital technology in the business and procurement world is a story of continuous innovation and evolution. Technology has constantly redefined who, between humans and machines, performed which activities. After a period of automating simple and repetitive tasks, progress allowed technology to increasingly impact more complex and collaborative activities that are the core of what knowledge workers do. AI is now creating a new type of collaboration between humans and machines, and this concept of ‘autogmentation’ reflects it. It is why parts 2, 3 and 4 of our series will dive deeper into what AI is and isn’t, whether or not it is different from other digital technologies and how it is used in business and procurement.

Read part 2 by registering for our free basic membership.

The remainder of the series is available by subscribing to our Insider membership.

Access Spend Matters dedicated ‘Artificial Intelligence in Procurement’ page for more AI insights.

AI in Procurement and 'Autogmentation'
AI - Artificial Intelligence