As of 2024, three of four businesses have adopted Artificial Intelligence (AI) to perform at least one business function. According to Forbes, this trend is expected to continue, with the AI market predicted to reach $1,339 billion by 2030. The widespread growth and adoption of AI will significantly impact procurement teams, with some estimates predicting up to 80% time savings on contact management through the automation of repetitive tasks like renewals and compliance regulations. Similarly, with the advancement of Generative Artificial Intelligence (GenAI), it is predicted that procurement teams will soon be able to reduce intake-to-source timelines by 95% or more. AI will drastically change how organizations manage procurement functions and help teams do more with less. Still, organizations often face resistance from procurement teams and need help to address the challenges of adopting AI into their procurement cycles.

While the future looks promising for the role of AI in procurement, this advancement in technology used by procurement professionals is a giant leap from the status quo. In the past, most legacy sourcing tools have been geared toward repetitive or time-consuming administration tasks that require human intervention. New tools leveraging AI automate these functions, shifting these tasks to more of a self-service model. This may leave some procurement professionals feeling like this technology is here to eliminate their jobs, leading to fear, mistrust, and resistance to change. 

Here, we'll explore five reasons why people resist AI in the procurement process and five strategies to overcome the challenges of AI adoption. 

1. Fear of the Unknown: Resistance to New Technology

As a concept, artificial intelligence can be traced back to the 1940s. Computers and machines that mimic human intelligence have long been discussed among mathematicians and scientists. Still, it has only been within the last 15 years that AI technology has been applied to everyday tasks, and only within the last year that Generative AI has been prevalent. What once were rule-based systems that comprised what is commonly thought of as early AI are now carefully architectured models using sophisticated multi-layered neural networks capable of image recognition, natural language understanding, and advanced learning. 

The journey to leverage AI at scale may be familiar territory for companies like Amazon, Apple, Google, and Tesla. Still, they have likely only scratched the surface of its potential, while many organizations are just beginning their implementation efforts. In an age where constant digital transformation is rapidly changing life and job functions, this can lead to technology anxiety. Defined as fear or apprehension experienced when faced with new or unfamiliar technologies, this phenomenon is not new to the procurement space. Many of the same worries and resistance regarding the use of AI in procurement are concerns the industry has grappled with before. For example, in the late 1990s and early 2000s, e-procurement platforms were introduced as one of the first ways to digitize procurement functions. This new technology was met with significant resistance from procurement teams - their fears centered around similar anxieties we see today: ethical and privacy concerns, loss of control, and job security. 

2. Lack of Understanding and Education: The Role of AI in Procurement

Many fears and anxieties about introducing or using AI in procurement functions are due to a lack of understanding and education. Misconceptions about how and when the technology will be used are often a symptom of limited knowledge of the tools' capability or how to adapt it to everyday functions. Previously, procurement teams have relied heavily on human judgment to handle both complex and routine tasks associated with sourcing events, as legacy tools and systems were incapable of replicating their human counterparts' expertise and decision-making abilities. Today, autonomous sourcing using AI technology allows organizations to remove repetitive and manual tasks from the buying process. Still, procurement professionals are unsure what that means for their day-to-day job functions. 

This disconnect between how AI tools are perceived and applied in the procurement cycle leads to friction in the adoption process. Until recently, AI was only considered in futurist applications, such as self-driving cars or robots meant to mimic human abilities. Now, organizations are realizing the potential of more practical applications, such as real-time data collection and demand forecasting. To remain competitive, procurement leaders will need to embrace AI and work to debunk common misconceptions. 

3. Ethical Decision-Making and Privacy: Procurement AI Concerns

With AI integration becoming a standardized business practice for many organizations, concerns about ethics and privacy are among the primary challenges of AI adoption for procurement teams. AI systems present unique ethical issues because they require a vast amount of data to function correctly in procurement. These systems, particularly those built to make autonomous decisions, are only as good as the data provided. While AI implementation can lead to significant cost-savings and shorter lead times, it can also compound existing data integrity problems. AI used in procurement cycles will make decisions or recommendations based on historical patterns in the data provided, which could inadvertently reflect biases within the organization's data. Similarly, if the tool is optimized for cost-savings, it may overlook critical supply chain factors such as sustainability or designated corporate social responsibility (CSR) goals in favor of more cost-effective options. 

Along with ethical concerns, data collection and privacy regulations are a top priority of procurement professionals considering the use of AI. When used as a function of the procurement cycle, AI systems rely on data collected from various sources to provide recommendations. This data includes supplier information, purchasing history, delivery schedules, and other sensitive information like contracts and communication patterns. With the prevalence of phishing attacks and data breaches, the improper collection, storage, and sharing of this data can open an organization to data misuse. This, in turn, can lead to more significant legal concerns if data privacy regulations such as GDPR are violated. 

4. Lack of Trust: AI Job Security Fears and the “Black Box” Problem

AI can automate many aspects of procurement functions, which may leave some employees questioning their job security and even fearing large-scale job losses. The thinking that AI will ultimately replace human involvement in the sourcing cycle leads procurement professionals to mistrust the technology entirely. AI tools are meant to be just that: a tool to help procurement teams scale. Repetitive, data-driven tasks such as contract management, data analysis, and supplier sourcing are candidates for automation. Value-added tasks such as long-term procurement strategies, tactical negotiations, and relationship building will still require human intuition.

Even though procurement jobs are safe, there is still much that we don't know about the inner workings of deep learning AI or what is referred to as the "black box" problem. This refers to the lack of insight into the system's internal decision-making process. AI systems are complex, with multiple neural network layers and unlimited data processing capacity. It may be hard to accept or rely on a system's choices without a clear explanation for procurement professionals who are used to justifying their decisions based on data, experiences, and relationships, particularly if a decision is reached that they don't agree with or if an unexpected outcome is produced.

5. Organizational and Cultural Barriers: Leadership Challenges in AI Adoption

It is estimated that a staggering 94% of senior business leaders suffer from technology anxiety, particularly around AI and machine learning. For leaders that have seen the dotcom boom, mobile devices, and the cloud functionally change how businesses operate over the last 35 years - another seismic shift can be daunting. However, with nearly 80% of enterprise businesses slated to adopt AI by 2026, we are at the forefront of yet another significant change. With procurement teams facing constrained resources and increased costs, it is up to leadership teams to find a solution that meets and exceeds demand. Now more than ever, organizations need to foster a culture of innovation that embraces AI and supports procurement teams through change. 

Culturally, many procurement organizations have fostered a risk-averse environment where AI adoption may be viewed as risky due to concerns about failure or unintended consequences. Organizations and leadership teams with a conservative approach to innovation may be tempted to stay with legacy systems and established practices, no matter how dated or cumbersome. The migration from complex and highly customized legacy systems to manage procurement functions may be seen as disruptive and costly, leading to company-wide resistance. Employees at all levels will likely be less open to embracing new technology if leaders are not fully committed to adopting AI.

Strategies for overcoming AI resistance

Many of the challenges of AI adoption faced by procurement teams and their respective organizations boil down to fear of the unknown and resistance to change. Implementing and adopting AI can be disruptive and even scary for established procurement functions using legacy systems in historically risk-averse organizations. 

Below are five strategies to address the challenges limiting AI adoption and overcoming AI resistance.  

1. Transparent and Frequent Communication:

Engage employees early and often in the AI innovation process. Transparent and open communication about the planning process and decision-making stages can significantly reduce anxiety around large-scale changes. 

Organizations will likely need collaboration across multiple lines of business, e.g., procurement, IT, finance, and any other supported departments. Cross-functional teams should be encouraged to work together by aligning on common objectives and sharing insights.

2. Build Trust and Demonstrate Benefits of Using AI:

Procurement teams must understand how AI will complement their work and act as a business partner rather than a competitor. Provide concrete examples of the activities the AI systems will perform and be prepared to explain that eliminating these manual tasks will free up time to be more strategic. 

Explain how the organization plans to measure implementation success and ROI using qualitative and quantitative metrics. This could include process efficiency metrics like reduced procurement cycle time or spend analytics like increased spend visibility. 

Showcase other successful implementations in organizations of similar size or industry. Social proof goes a long way in building trust for a skeptical audience. For example, Alcoa, an organization with 135 years of history and 27 operating locations, was able to deploy an AI implementation in just four months and, within one year, saw almost nine times the ROI.

3. Comprehensive Training and Educating for Employees:

Equip employees with a basic understanding of AI and what it is capable versus incapable of doing in the procurement cycle. Enabling AI literacy will help make it less intimidating by providing a clear idea of its function within the organization. 

Procurement professionals should be trained to interpret AI insights, oversee automated processes, and perform any other function related to their job. This may help them realize the full potential of AI implementation in their daily activities. 

Additionally, creating an internal wiki or knowledge center to house frequently asked questions, resources, policies, and product documentation will help encourage teams to explore and use the technology at their own pace.

4. Address AI Concerns:

Don't be afraid to answer the hard questions about ethical usage and data privacy. Procurement professionals are adept at identifying risk and will likely have concerns about AI systems having access to sensitive and extensive datasets. 

Organizations should establish ethical guidelines and robust data privacy policies for using AI in procurement. These guidelines and policies should consider broader goals related to CSR initiatives, along with practical applications such as anonymizing sensitive data and third-party sharing with outside vendors.

Providing procurement teams with strategies for oversight will help alleviate some of the anxieties about AI implementation and fears of widespread adoption. Organizations are adopting what is called the Human in the Loop approach, which is now widely considered a best practice when leveraging AI or machine learning in business functions. Humans monitor AI processes to provide high-level supervision and guidance to handle edge cases or high-stakes scenarios. AI might be intelligent, but it still lacks the judgment and expertise that only seasoned procurement professionals can provide. Developing training and strategies for monitoring and gut-checking AI systems will help build confidence in the technology.

5. Foster a Positive Change Culture:

Above all, organizations can help their employees through AI adoption challenges by creating a culture of innovation and adaptability. Experimentation with AI should be encouraged - this mindset will help facilitate learning opportunities that may otherwise be seen as failures. Creating room for experimentation and testing will reduce the fear of failure and encourage teams to try new tools. 

There will likely be team members who are excited about the prospect of integrating AI into their everyday work. That enthusiasm should be fostered and celebrated. Early adopters can lead by example and entice others to follow suit. 

Adopting AI is Challenging

Implementing new technology into a procurement function will be challenging, no matter what. Humans are predisposed to resist change. Implementing what may be considered "risky" new technology inherently goes against the procurement professionals' instinct to reduce risk. The uncertainty around AI adoption in procurement functions stems from fear of the unknown, lack of understanding, and general anxiety about the functionality of new systems. It is up to senior leadership within organizations seeking to implement AI technology to create an adoption environment. 

If your organization seeks to implement and adopt AI, consider using one or more of the strategies above to overcome AI resistance and aid in the transition period. AI may be advanced technology capable of human-like decisions, but it is only as good as the humans who use it.