To acknowledge and celebrate the end of the Falklands war on 14 June 1982, we are publishing this story about the unlikely friendship of two amateur radio enthusiasts 8,000 miles apart that allowed more than 50 soldiers the opportunity to get messages home to their loved ones. Disclaimer: This story was originally brought to light by bfbs Forces News on 7 December 2022. Certain linguistic changes have been made in the subsequent article from Cambridge Management Consulting, but all of the information comes from the original article, written by Hannah King Ros Moore, which you can read here , and an accompanying video on their YouTube page, which we encourage you to watch . Between April and June 1982, Argentina and the United Kingdom engaged in a 10-week conflict which would come to be known as the Falklands War. Battling over the sovereignty of the Falkland Islands and its territorial dependency, South Georgia and the South Sandwich Islands, the conflict began with the invasion of the former by Argentina on 2 April, and ended with their ultimate surrender on 14 June – Falklands Liberation Day. During this time, more than 100 villagers were being held captive in a hall by the Argentinians for almost seven weeks, before being free on 29 May by 2 PARA, following a battle to take Goose Green. Eighteen British soldiers were sadly lost during this fight, but back at home their families had heard nothing since the soldiers set sail. That was until the unlikely friendship of two amateur radio enthusiasts 8,000 miles apart allowed more than 50 soldiers the opportunity to get messages home to their loved ones. Bob McLeod, a ham radio operator, had already made history by making the announcement to the world that the Falkland Islands had been invaded. However, in doing so, he had also drawn the attention of the Argentinians, who were quick to confiscate his equipment. Alan Bullock was the Forward Observation Officer of D Company, 2 PARA, and, while walking through the main street of Goose Green, spotted an antenna on a house belonging to Bob. Alan knocked on Bob’s door, “Hello… is there any chance you are a radio amateur?” “Yes… But the Argentinians took my transmitter and smashed it up.” Bob’s wife then suggested that they use his 50W amplifier that was safely hidden under the stairs. As Forward Observation Officer, Alan had his state-of-the-art at the time, military clansman radio, which, although only 20 watts for communicating over short distances, could be combined. In order to get messages back to the UK, Bob made contact with John Wright, a radio amateur in Oxford with whom he had been chatting to over the airwaves for many years. Together, Bob and John devised a cryptic code for their conversation and each transmitted on different frequencies, in case anyone was listening. John would be given a soldier’s phone number and short messages to pass on to his family. John said of the plan: “Normally amateur radio enthusiasts talk about their radio equipment, experiments they’re doing. “In this case, the communication was to pass family traffic which, under normal circumstances, isn’t allowed, but I threw caution to the wind and did what I could as quickly and clandestinely as possible.” Word quickly got around the troops and soon it wasn’t just D Company’s families Bob and John were contacting. Before long, there was a queue outside Bob’s door, with each message always the same: "I am safe." About BFBS BFBS is a pioneering military charity with a mission to entertain, inform, connect and champion the UK armed forces, their families and veterans. Our armed forces do a tough yet invaluable job, often working in extreme conditions – so BFBS believes they deserve our unfailing support. Find out more at: https://about.bfbs.com/ The Positive Impact of Telecommunications This story, and the combined initiative, intuition, and innovation between Allan Bullock, Bob McLeod and his wife, and John Wright, is testament to the transformative power of technology for forging connection and bringing optimism at times of difficulty, danger, and otherwise disconnect. This story is particularly inspiring for Cambridge Management Consulting as an organisation currently working hard to enhance the telecommunications and technology infrastructure of the Falkland Islands. For more information about how we are achieving this, you can read about our consultancy work on the Islands here , and the opening of Falklands IT here .

Disruption now occurs with unprecedented regularity, as industries are upended not by traditional competitors but by unexpected entrants wielding innovative technologies and business models.  The difference between thriving and becoming obsolete increasingly hinges on your organisation's ability to anticipate and adapt to disruption before it's too late. The Ur-case of this was Blockbuster, who ignored the threat of streaming technologies, and specifically Netflix (which it could have bought), until it was far too late to pivot and catch up. Our article explores how businesses can develop strategies that offer predictions and agility, embedding creativity and insight into frameworks and actionable steps that plot a course through the disruptive landscapes of the next few years and beyond. Understanding the Nature of Disruption Disruption is no longer just a buzzword — or the philosophy of ‘break things and move fast’ that drove the early tech start-ups that now dominate our waking lives. The theory of disruptive innovation, popularised by Harvard Business School professor Clayton Christensen, explains how new technologies, products, or services can start small but eventually surpass established offerings in existing markets[1]. This process typically begins when smaller companies with fewer resources challenge established or traditional businesses by addressing underserved market needs[5] in new ways; usually with business models that bypass normal routes to market and allow these companies to scale at pace. Recent examples include: fintech banks that challenge the need for brick-and-mortar; online over-the-top media applications that replace the need for print media and traditional broadcast television; digital media and the success of subscription models, replacing physical media for music, films and other forms of entertainment; and platform apps like Uber, which connect us to a fleet of independent drivers who are paid per ‘gig’ and regulated by a ratings system. Today's notion of disruption is characterised by several key features: Accelerated Pace of Change The pace of disruption has accelerated beyond anything previously seen, with transformative technologies reaching mainstream adoption faster than ever[15]. While it took decades for technologies like electricity and telephones to achieve mass adoption, modern innovations like smartphones and AI have transformed entire industries in just a few years. Cross-Industry Disruption Disruptive threats increasingly come from outside traditional industry boundaries. Companies must now monitor not only direct competitors but also adjacent industries and completely unrelated sectors where transferable innovations might emerge[15]. For example, tech giants have disrupted financial services, retail, healthcare, and automotive industries without prior experience in these sectors. Technology-Enabled Business Models Today's most powerful disruptions combine technological innovation with business model innovation. Examples include: Platform models: Uber revolutionised transportation by connecting riders and drivers through a user-friendly mobile app, utilising independent drivers who pay for their own vehicles for rapid scalability[1]. Subscription services: Netflix and Spotify transformed entertainment consumption by shifting from physical media to on-demand streaming with personalised algorithmic content recommendations[1]. Direct-to-consumer approaches: Tesla's direct sales model bypassed traditional dealership networks while integrating advanced electric vehicle technology and autonomous capabilities[1]. From Traditional to Adaptive Strategy Traditional strategic planning approaches — characterised by multi-year roadmaps and rigid implementation plans — have become increasingly inadequate in today's fast-moving business environment. We look at some of the challenges businesses now face below. The Limitations of Traditional Strategy Conventional strategies often fail because they: Assume relative stability in market conditions Take too long to develop and implement Lack flexibility to respond to unexpected changes Rely heavily on historical data to predict future outcomes The Adaptive Strategy Advantage Adaptive strategy, often described as the "Be Fast" approach, emphasises agility, experimentation, and continuous evolution[3]. This approach thrives in fluid industries with high uncertainty and a fast pace of change, such as technology, fashion, entertainment, and start-ups[3]. Organisations that embrace adaptive strategies gain significant advantages: Higher profitability: Companies ranking high in adaptability enjoy up to 75% higher profitability than their less adaptive counterparts[10]. Faster market response: Adaptive firms achieve approximately 60% faster time-to-market compared to traditional competitors[10]. Innovation capacity: The ability to experiment boldly and rapidly iterate creates an environment where breakthrough innovations are more likely to emerge[10]. Real-World Adaptive Strategy Success Consider Netflix's journey from DVD rental service to streaming giant to content producer. Rather than creating a 10-year plan, Netflix constantly evolved based on emerging technologies, customer preferences, and market opportunities. This adaptive approach allowed them to pivot whenever necessary while maintaining their core value proposition of convenient entertainment access[1]. A New Framework for Ensuring Strategy Relevance To maintain strategic relevance amid disruptive trends, companies need a systematic framework that balances stability with flexibility. Anticipate Disruption Through Trend Analysis Successful businesses identify potential disruptions before they manifest fully by monitoring Hard Trends — future certainties based on measurable facts[15]. These include demographic shifts, technological advancements, and regulatory changes that provide predictable directional guidance. For example, financial services firms that recognised the Hard Trend of increasing digital connectivity were better positioned to respond to the rise of mobile banking and fintech disruption. Build your Agility Organisational structures and processes must be designed to support rapid adaptation: Decentralised decision-making: Empower teams closest to customers and market changes to make decisions without lengthy approval chains[3]. Cross-functional collaboration: Break down silos between departments to enable faster information sharing and coordinated responses to change[3]. Agile methodologies: Adapt software development approaches like sprints, continuous integration, and iterative testing to broader business strategy[3]. Foster a Culture of Innovation Innovation cannot be an isolated function — it must permeate your entire organisation: Encourage experimentation: Create safe spaces for testing new ideas with minimal bureaucracy and fear of failure[3]. Customer-centric innovation: Ground innovation efforts in a deep understanding of customer needs rather than internal assumptions[14]. Structured innovation processes: Establish clear pathways for moving ideas from conception to implementation while maintaining flexibility[14]. KPIs that support innovation: For example, looking at the value of a portfolio of innovations rather than a specific innovation project. Leverage Data & Technology Data-driven insights provide a vital competitive advantage in your disruption response: Real-time market intelligence: Deploy advanced analytics to detect weak signals of change before they emerge fully-formed[3]. Predictive modelling: Use Agentic AI to identify patterns and forecast potential disruptions[2]. Digital transformation lifecycle: Invest in the necessary expertise and infrastructure to undertake on-going programmes of transformation — a big step, and potentially expensive, but it can help immunise your business against disruptive technologies and new models. Practical Implementation Steps Translating disruption awareness into effective action requires specific tactical approaches.

Welcoming Simon Crimp Cambridge Management Consulting is delighted to welcome Simon Crimp as Managing Partner and Lead for our Digital Transformation practice. With more than 25 years of international technology leadership, Simon joins us at a pivotal moment as our clients seeking to drive meaningful change across their portfolios. His extensive experience spans hands-on technology operation and engineering, setting global technology strategy, and C-suite advisory, positioning him as a powerful asset for businesses navigating the next wave of digital innovation. Simon began his career in the demanding world of capital-markets technology, supporting trading floors at JP Morgan and managing service delivery across major exchanges. This early immersion laid the groundwork for a deep technical understanding and an ability to deliver resilient, high-availability systems in some of the world’s most high-pressure environments. His next chapter at Euronext LIFFE (now part of ICE Futures Europe) saw him rise through the ranks from service management to become Global Head of Systems Engineering. There, he was instrumental in delivering two state-of-the-art data centres and modern trading infrastructure, ensuring the reliability and resilience required by global financial markets. The next decade of Simon’s career took him to IG Group, where he led the transformation of infrastructure and operations on a global scale. As Head of Infrastructure & Operations and later Regional CTO and Global Head of Shared Technology Services, Simon architected IG’s pioneering hybrid cloud strategy, orchestrating seamless integration across AWS, Google Cloud, and multiple colocation facilities. He didn’t just modernise technology, he reshaped how teams operated, leading over 400 technologists across regions, managing a significant budget, and redesigning operating models to accelerate delivery while enhancing security and compliance. Notably, Simon developed IGs Security Operations and Cyber Defence function, further strengthening the company’s posture in a fast-evolving threat landscape. His versatility was clear during his tenure as Interim CEO and Head of the Japan Office, where he secured C-level buy-in for localisation and expansion into new markets. Before leaving IG in 2024 Simon developed the Data Strategy for the company and led build out of the Data and AI capability into GCP. Beyond his technical and commercial expertise, Simon has invested in leadership development, qualifying as an Executive Coach at Henley Business School. This enables him to drive not only digital transformation, but the cultural shifts essential for lasting impact. This helps organisations embed agile, product-focused ways of working alongside technology renewal. Reflecting on his decision to join Cambridge Management Consulting, Simon shares: “I’m really excited to get the opportunity to take 25 years of technology and organisational transformation across Finiancial Services and Fintech into new industries and markets. Cambridge MC has had great success since opening its doors, and I’m thrilled to be part of the leadership team that will drive the next phase of growth.” In this new role he will lead end-to-end digital transformation programmes — from initial vision and business case to execution and ongoing improvement. He will focus on orchestrating cloud-first, data and AI strategies, embedding modern operating models, guiding post-merger technology integration, and advising boards on security, compliance, and the adoption of emerging technologies. Whether your organisation is looking to modernise legacy estates, scale digital operations globally, or embed new ways of working, Simon Crimp and the Cambridge Management Consulting team are ready to help drive value at any stage of the programme. To connect with Simon and explore how he can support your digital transformation journey, reach out to us at info@cambridgemc.com or scrimp@cambridgemc.com

Introduction In today's interconnected world, submarine cable networks form the backbone of global communication, enabling the seamless exchange of data across continents. While these undersea cables are the epitome of engineering marvels, their effectiveness hinges not only on the ‘wet' network in the seabed, but also on the often-overlooked terrestrial network backhaul. The terrestrial backhaul — the infrastructure that connects submarine cable landing stations to inland data centres and networks — is as crucial as the submarine network itself. Proper management and handling of terrestrial backhaul partners is essential to ensure the optimal performance, cost-efficiency, and security of all submarine networks. The Vital Importance of Backhaul Management Submarine networks are only as strong as their weakest link, and the terrestrial backhaul is a pivotal link in this ecosystem. Without a well-designed and managed backhaul, even the most sophisticated submarine network can face inefficiencies, bottlenecks, and vulnerabilities.  Key reasons why managing terrestrial network backhaul partners is so critical include: Cost Optimisation Terrestrial backhaul costs constitute a significant portion of the total network expenditure. Poorly negotiated contracts or suboptimal supplier relationships can inflate operational costs, diminishing the overall profitability of submarine networks. Network Performance The design, quality, and reliability of terrestrial backhaul networks directly affect latency, throughput, and overall user experience. A poorly managed partner ecosystem can lead to performance degradation, affecting service delivery. Security and Risk Mitigation The terrestrial segment is often more vulnerable to physical and cyber threats compared to submarine cables. Effective partner management ensures that security measures are prioritised, and risks are mitigated. Scalability and Flexibility As data demands grow, submarine networks must scale effectively. Well-managed terrestrial backhaul partners enable seamless scaling and adaptability to meet changing requirements.

Procurement, like many other sectors, is currently being transformed by AI technologies. Organisations are rapidly adopting AI solutions to enhance efficiency, reduce costs, and gain a competitive advantage in their procurement processes. According to recent research by Economist Impact, AI tools are already helping procurement professionals at 64% of firms, with larger organisations leading this digital transformation [7]. However, given the challenges of effectively implementing AI tools and their tendency to produce inaccurate or misleading outputs, it is essential for organisations to critically assess the immediate value of this technology, the costs involved in its deployment, and the potential impact on procurement teams. This article explores the user cases of AI in procurement, the emergence of Agentic AI, implementation challenges and strategies, and how Cambridge Management Consulting can guide you through this complex process and over the hurdles. We also stress that AI in procurement is not a panacea — it can be leveraged successfully for certain user cases when it is integrated with the support of well-trained teams who can spot errors and who understand the limits of these tools. Let's Start with the Limits AI, despite the marketing hype in the media, is not yet a ‘silver bullet’ or an all-encompassing fix when it comes to procurement. It will not solve everything on day one, but it will change how a procurement function operates and will no doubt drive efficiency alongside data accuracy and linkage. Now, more than ever, having a skilled Procurement team alongside cutting-edge technologies like AI is essential for unlocking new efficiencies and elevating procurement to the next level. AI will make a procurement team even more data driven in their analysis and decision making. AI tools will allow procurement teams to sift through vast amounts of data quickly and will draw conclusions for review and assessment. The power of being data driven should not be underestimated and as the American composer and economist W. Edwards Deming once said, “Without data, you’re just another person with an opinion, […] in God we trust; all others bring data” [22]. Each and every organisation must carefully consider how to leverage AI-generated data effectively. While AI can enhance procurement processes, an experienced procurement team remains essential for defining and prioritising key challenges, navigating contract negotiations, and implementing structured cost-reduction strategies. The human touch — particularly in managing and driving commercial supplier relationships — will continue to be a vital component of procurement. While relationship management may not be the single most important aspect of supplier management, it is undeniably critical. It encompasses relationship-building, communication, collaboration, and trust: elements that are fundamental to maximising supplier value and mitigating risks. Supplier management is more than just overseeing transactions; it demands a proactive approach that fosters strong partnerships. AI can revolutionise data management, but it must be complemented by the human expertise that ensures strategic decision-making, relationship stewardship, and long-term supplier success. One could argue that it is easy to get lost in an AI discussion or defining a procurement strategy, but bottom-line supplier relationship management is critical and integral for any procurement department to be successful. If you cannot build, leverage and maintain relationships, you shouldn’t be at the table. The Current State of AI in Procurement Generative AI (GenAI) is having the same disruptive effect in procurement that it is in many other business areas, initially by completing quite simple tasks with incredible speed, accuracy and efficiency. This includes automating routine tasks, providing actionable insights from data sets, and freeing up time for your teams to focus on higher-level tasks such as managing processes and vendor relationships. Below we highlight which tasks can be successfully enhanced or supported by AI. AI-Powered Procurement Automation For business leaders, AI is the tireless digital assistant that procurement teams have long needed. By automating tedious tasks like purchase order processing, linking third-party costs back to revenue services to strive for gross margin clarity, invoice management, and contract administration, AI frees professionals to focus on strategic initiatives. The impact is substantial: according to recent data, 45% of AI investments in procurement are focused on contract automation, highlighting organisational priorities for efficiency improvement and error reduction [1]. Real-world implementation has shown significant results. For example, a global manufacturing company deployed AI to automate invoice processing, reducing errors by 80% and cutting processing time by half [1]. Data-Driven Decision-Making AI spares procurement from wading through hours of paperwork, a process that is time-consuming and prone to cascades of errors. Rather than being overwhelmed by huge data sets and unsure on which useful information to extract, AI does this with much more precision and many orders of speed. With AI-driven analytics, procurement teams can manage and link multiple data sets, identify trends, and make more informed purchasing decisions in real time. McKinsey reports that procurement leaders implementing AI-driven analytics have accelerated supplier selection by 30%, demonstrating the significant impact on workflow efficiency [1]. The Rise of Agentic AI in Procurement While traditional AI has already made significant inroads in procurement, a more advanced form — Agentic AI — is now emerging as a step-change for the profession. What is Agentic AI? Agentic AI represents the next phase in artificial intelligence models. Unlike previous automation tools that require human oversight for key decisions, AI agents can operate independently, leveraging machine learning, predictive analytics, and natural language processing to interact with suppliers, assess risks, and optimise sourcing strategies with minimal supervision[4]. According to The Hackett Group's 2025 Procurement Agenda and Key Issues Study, Agentic AI is the top trend impacting procurement this year, alongside digital procurement and automation[4]. The technology is expected to disrupt nearly 50% of procurement activities over the next five to seven years, creating entirely new opportunities for strategy[4]. The outlook for procurement teams might be more climatic, depending on the consistency and accuracy of Agentic AI. These models will be capable of independent reasoning and it currently unclear how close this will bring us to Artificial General Intelligence (AGI). Adoption Trends and Strategic Focus The shift in Agentic AI from concept to a reality might be surprisingly rapid. A recent survey by ProcureCon found that 90% of procurement leaders are considering AI agents for optimising their procurement functions[4]. This technology is becoming central to orchestrating complex procurement activities with unprecedented efficiency — from sourcing and contract negotiations to spend classification, supplier onboarding, compliance, and risk assessment. There is relatively little data or evidence at this point to suggest the likely error-rate among these agents and to what degree all results and actions will need to be checked and validated by human teams. It is also underappreciated that in order to successfully implement AI, businesses must have set up basic data structures, metadata, and processes. A significant number of companies are not yet ready to adopt these technologies and must get their house in order first. Implementation is a potentially complex and expensive task, requiring long phases of design and testing to fine-tune the outputs. Benefits of AI Procurement The adoption of AI in procurement delivers multiple advantages that will enhance organisational performance across various metrics. We look at the key advantages below: Cost Reduction & Efficiency Gains AI implementation in procurement delivers measurable financial benefits. McKinsey highlights a 10% reduction in procurement costs through AI adoption[1]. By automating routine tasks, businesses reduce labour costs while simultaneously increasing throughput and accuracy. Enhanced Supplier Management AI transforms supplier relationships by providing deeper insights into supplier performance, risk profiles, and market dynamics. This enables procurement teams to make more informed decisions about supplier selection, negotiation strategies, and relationship management. Agentic AI will bring predictive analytics that will be able to flag and correct issues in your supply chain before they occur. Improved Risk Management Leading AI platforms apply advanced machine learning techniques to uncover signals in supplier data that indicate potential disruptions, from financial issues and bankruptcy risks to geopolitical challenges, climate events, and cyber threats. This allows procurement teams to mitigate risks proactively rather than reactively, creating a significantly lower threat to spend, compliance and reputational damage[6]. Contract Intelligence Natural language processing tools extract insights from legacy contracts and external databases to benchmark terms. AI can negotiate agreements with suppliers in real-time chat sessions, optimise renewals, and highlight risks — significantly reducing the manual burden on procurement teams. Smart contracts can then self-execute when conditions are met and provide comprehensive audit trails[6]. See our separate article on AI in Contract Management for more details: https://www.cambridgemc.com/how-to-successfully-integrate-ai-into-your-contract-lifecycle-management Challenges in Implementing AI in Procurement Despite the clear benefits, companies face several significant challenges when implementing AI in their procurement functions. Data Quality & Availability AI systems require vast amounts of accurate data to function effectively. Many supply chains struggle with data silos and inconsistent formats, making it difficult to create the comprehensive, high-quality datasets needed for AI[2]. Data fragmentation across different systems — legacy platforms, ERP systems, sensors, and IoT devices — creates integration challenges that can undermine the effectiveness of AI [8]. Integration with Existing Systems Many legacy procurement systems were not designed to integrate with modern AI technologies, leading to compatibility issues and potential disruptions in system functionality [2]. This technical challenge often requires significant IT resources to overcome. Implementation Costs Implementing AI involves substantial initial expenses for software, hardware, and skilled personnel. Additionally, there are ongoing costs to retrain AI models as business environments evolve [2]. These financial considerations can be barriers to adoption, particularly for smaller organisations. Internal Resistance Resistance to adopting new technologies often stems from a lack of understanding, fear of job displacement, or discomfort with changing established workflows[2]. This human factor can significantly slow or derail AI implementation efforts if not properly addressed with training, careful messaging and change management methodologies. Data Security Concerns As AI systems process sensitive procurement data, including confidential pricing information and intellectual property, security becomes a critical concern. Businesses must engage comprehensive data protection measures while still enabling AI systems to access the information they need. Responsible AI As well as data security concerns, there is also a strong need and argument for companies to strive for fitness and non-discrimination when it comes to AI. Companies should have an AI Risk and Assessment process in place to ensure that data bias is avoided and that ethical guidelines when it comes to data analysis and management are followed. The ‘AI Ethics Guidelines Global Inventory (AEGGI)’, created by Algorithm Watch, currently contains 167 sets of principles and guidelines, which it recommends should be followed, and there are also responsible AI training tools available, such as Google’s ‘People & AI Guidebook’ and Omidyar Networks ‘Ethical Explorer’, that can be used. Additionally, new legislation is also being introduced, for example, the ‘EU’s Artificial Intelligence Act’, to ensure that AI is used responsibly. It’s widely acknowledged that 8 core principles should be assessed and evaluated when developing AI accountability [20]: Privacy & Security Reliability & Safety Transparency & Explainability Fairness & Non-discrimination Professional Responsibility Human Control Promotion of Human Values Strategies for Successful AI Implementation To overcome implementation challenges and maximise the benefits of AI in procurement, you should consider the following strategies: Establish Strong Data Foundations Before diving into AI adoption, you must ensure that your business has the right data infrastructure in place. This includes: Improving data quality, governance, and standardisation Integrating disparate data sources Establishing real-time data capabilities, which are prerequisites for effective AI implementation[4] Implementing foundational tools like spend analysis and decision optimisation[1] Take a Targeted Approach Rather than attempting wholesale transformation, you should: Identify specific areas where AI can complement existing processes Focus initial implementation on high-value, low-complexity use cases Use AI where it adds the most value rather than applying it universally [1] Consider a phased implementation approach Address the Human Element Successful AI implementation requires careful attention to the people involved: Equip your workforce with the skills to leverage AI effectively Implement comprehensive change management strategies Educate employees about how AI will enhance their roles rather than replace them Rethink how procurement teams interact with AI-driven systems [4] Balance AI with Human Intelligence The most effective procurement functions will be those that: Combine the efficiency of AI with human judgment and expertise Preserve crucial human skills in negotiation, relationship management, and strategic decision-making Use AI to augment human capabilities rather than replace them entirely [1] Create collaborative human-AI workflows that maximise the strengths of both approaches Conclusion: Blending AI & Human Expertise AI is fundamentally reshaping procurement, transforming it from a primarily transactional function to a strategic and predictive driver of value. From automating routine tasks to enabling sophisticated predictive analytics and autonomous decision-making, AI technologies are creating unprecedented opportunities for efficiency, intelligence, and innovation. While implementation challenges exist, businesses that approach AI adoption strategically, with proper attention to data foundations, targeted use cases, and human factors, can realise significant benefits. As we look into the near future, the most successful procurement functions will be those that effectively blend AI capabilities with human expertise, creating a powerful synergy that drives an ongoing competitive advantage. Cambridge MC: Your Partner for AI-Powered Procurement Implementing AI in procurement requires specialised expertise and experience. Cambridge Management Consulting (Cambridge MC) offers you the guidance needed to navigate this complex transformation successfully. We have dedicated Data and AI teams as well as a deep background in procurement and contract management expertise. Comprehensive Implementation Support Cambridge MC offers: Strategic assessment of procurement AI opportunities Roadmap development for AI implementation Integration of AI solutions with existing procurement systems Change management support to ensure successful adoption Ongoing optimisation of AI-powered procurement processes Get in touch with Andy Everest or one of our procurement experts to discuss your current needs and any issues pertaining to AI and procurement. Use the form below or email: aeverest@cambridgemc.com . Visit our Commercial & Procurement page: https://www.cambridgemc.com/procurement-and-commercial Citations [1] https://consultingquest.com/insights/generative-ai-in-procurement/ [2] https://www.linkedin.com/pulse/6-key-challenges-ai-implementation-supply-chain-industry-chris-clowes-1r67c [3] https://www.oracle.com/scm/ai-in-procurement/ [4] https://www.gep.com/blog/technology/agentic-in-procurement-overview-benefits-implementation [5] https://futuria.ai/futuria-and-cambridge-management-consulting-announce-innovative-ai-driven-partnership/ [6] https://www.gep.com/blog/technology/how-ai-is-revolutionizing-the-procurement-cycle [7] https://impact.economist.com/perspectives/strategy-leadership/ai-demands-new-era-procurement-skills [8] https://www.qservicesit.com/9-common-challenges-in-supply-chain-management-with-ai [9] https://precoro.com/blog/ai-in-procurement/ [10] https://www.cio.com/article/3853910/how-agentic-ai-can-deliver-profound-transformation-in-procurement.html [11] https://www.cambridgemc.com/futuria-and-cambridge-management-consulting-announce-innovative-ai-driven-partnership [12] https://www.spendflo.com/blog/ai-in-procurement-orchestration [13] https://media-publications.bcg.com/BCG-Executive-Perspectives-Future-of-Procurement-with-AI-2025-27Feb2025.pdf [14] https://pmc.ncbi.nlm.nih.gov/articles/PMC11788849/ [15] https://www.cappo.org/news/660146/Pros-and-Cons-of-Using-Artificial-Intelligence-for-Procurement.htm [16] https://pactum.com/understanding-agentic-ai-in-procurement-how-autonomous-ai-has-been-transforming-supplier-deals/ [17] https://digitalisationworld.com/news/67692/qarbon-technologies-collaborates-with-cambridge-management-consulting [18] https://www.coupa.com/blog/ai-in-procurement/ [19] https://suplari.com/10-procurement-job-roles-most-impacted-by-ai/ [20] https://stockiqtech.com/blog/disadvantages-ai-supply-chain/ [21] ‘ Responsible AI: Principles and Practical Applications ’ – LinkedIn Course, By: Tsu-Jae Liu, Brandie Nonnecke , and Jill Finlayson ( https://www.linkedin.com/learning-login/share?forceAccount=false&redirect=https%3A%2F%2Fwww.linkedin.com%2Flearning%2Fai-accountability-build-responsible-and-transparent-systems%3Ftrk%3Dshare_ent_url%26shareId%3DhTdANzytTi28DI30mdTN%252BQ%253D%253D ) [22] Top 200 W. Edwards Deming Quotes (2025 Update). QuoteFancy . https://quotefancy.com/w-edwards-deming-quotes.