The Globality Blog

The statistics tell an alarming story: according to IBM's 2024 Cost of a Data Breach Report [1], the average cost of a data breach has now reached $4.88 million. The report highlights an emerging concern: attackers are increasingly leveraging AI and automation tools, adding complexity to the threat landscape and extending breach lifecycles by weeks or months.

But beyond these numbers lies a more nuanced reality; as AI transforms business processes, it creates novel attack surfaces and security challenges that traditional frameworks struggle to address. The rapid adoption of AI technologies across industries has fundamentally changed the security landscape, introducing complexities that weren't even contemplated in traditional security frameworks. Organizations now face the dual challenge of protecting not just their data, but also the AI models that process it, the training data that shapes these models, and the outputs they generate.

At Globality, we've learned that robust security isn't just about checking boxes; it's about building a comprehensive shield around customer data that evolves with emerging threats. While we're proud of our ISO 27001 certification and SOC2 compliance (both recently reaffirmed through rigorous audits), we see these as foundations rather than finish lines. These certifications represent our commitment to maintaining rigorous security standards, but our actual security practices go well beyond what these frameworks require. We've built our security infrastructure with the understanding that in today's landscape, compliance is merely the starting point.

Beyond Standards: Security in Practice

The rise of AI has introduced new complexities in data protection that few organizations are fully prepared to address. Traditional security models often fall short when confronted with the unique challenges of AI systems.

Data residency requirements have become increasingly complex, varying not just by country, but by data type and processing stage. Organizations must now track and control data flows across multiple jurisdictions, ensuring compliance with a patchwork of regulations while maintaining system performance. This becomes particularly challenging when AI models need to process data across borders or when training data comes from multiple jurisdictions.

The protection of both training data and model outputs presents another layer of complexity. At Globality, we've developed sophisticated approaches to this challenge. Our AI models fall into two main categories; classifiers for categorizing projects based on natural language descriptions, and clustering/ranking models for provider matching. Each requires its own careful security consideration. For classifier training, we've implemented a rigorous four-step anonymization and sanitization pipeline:

• We systematically remove client-specific identifiers and codes
• We employ Named Entity Recognition (NER) to identify and remove personal and company proprietary information
• We use sophisticated techniques like Normalized Google Distance (NGD) calculations to identify and redact client-specific entities
• We implement reproducible name mangling for sensitive terms

This process, performed with heavy involvement by Globality InfoSec personnel, ensures that while our models can learn from aggregate patterns, they never retain or expose sensitive client information. We're particularly stringent about personal identifiable information (PII); it's completely excluded from our training pipeline.

For our clustering and ranking models, which process a wide array of supplier data, we've implemented strict controls on data sourcing and usage. While we collect data from public, private, and proprietary sources, we maintain clear boundaries around what data can be used for model training. We've explicitly designed our systems to exclude sensitive proprietary data from model training without explicit customer consultation and approval.

Ensuring AI systems maintain security during both training and inference requires a comprehensive approach that traditional security frameworks don't fully address. During training, we must protect against data poisoning attacks and unauthorized access to training data. During inference, we need to guard against model extraction attacks and ensure that model outputs don't leak sensitive information.

To address these challenges, we've implemented advanced security measures that go beyond standard practices. For example, our Hold Your Own Key (HYOK) encryption capability gives customers complete control over their data while maintaining functionality, and our AI Governance Committee provides oversight of all AI changes from model improvements to prompt evaluation.

IP allowlisting is another critical component of our security infrastructure that we've implemented as part of a broader zero-trust architecture to protect every point of ingress (including both web application and REST API requests). This means every access attempt, whether from an allowed IP or not, undergoes rigorous authentication and authorization checks. We've also adopted the ISO 42001 framework for AI systems, ensuring security is built into our AI operations from the ground up, not bolted on as an afterthought.

Practical Security Advice for the AI Era

Based on our experience protecting sensitive enterprise data, we've developed a comprehensive set of security principles that organizations should consider as they build out their AI infrastructure:

• Treat AI model inputs and outputs with the same rigorous security controls as your raw data. Many organizations focus on securing their databases but leave model interactions inadequately protected. This creates vulnerabilities that sophisticated attackers can exploit. Recent research has demonstrated how seemingly innocuous model outputs can potentially be used to reconstruct training data [2]. That's why we've implemented end-to-end encryption for all model interactions, ensuring that data remains protected at every stage of processing.
• Implement granular access controls as part of a comprehensive zero-trust architecture. IP allowlisting is just the beginning; every access request should be validated regardless of its source. This means implementing strong authentication mechanisms, regular access reviews, and detailed audit logging. At Globality, we maintain comprehensive audit trails of all system access, enabling us to detect and respond to potential security incidents quickly.
• Encryption should be end-to-end, with customer control over keys. Our HYOK implementation demonstrates that robust encryption doesn't have to come at the cost of functionality. We've developed sophisticated key management systems that allow customers to maintain complete control over their data while still leveraging our AI capabilities. This includes automatic key rotation, secure key storage, and immediate revocation capabilities.
• Implement comprehensive data anonymization pipelines for AI training. This isn't just about removing obvious identifiers; it requires a sophisticated multi-layer approach that considers context and relationships between data points. Our experience shows that effective anonymization must combine rule-based systems, machine learning techniques, and careful human oversight.
• Embrace data minimization as a fundamental security principle. At Globality, we rigorously define what data we need and only use the data required. We also carefully select our models and vendors, and we don't allow third parties to use any data we send through their APIs for AI training. This approach follows a core security principle: the best way to mitigate risk is to minimize the data you hold in the first place. By being intentional about data collection and processing, organizations can significantly reduce their attack surface and potential exposure.

The Path Forward

The reality is that security in the AI era requires a fundamental shift in how we think about data protection. It's not enough to secure static data; we need to protect information as it flows through increasingly complex AI systems. This means implementing security controls that understand and account for the unique characteristics of AI workflows, from data ingestion through model training and inference.

Our commitment to security at Globality goes beyond maintaining certifications and implementing standard security measures. We're continuously evolving our security infrastructure to address emerging threats and protect our customers' data in an increasingly complex technological landscape. By sharing our experiences and insights, we hope to contribute to the development of more robust security practices across the industry.

This approach has not only helped us maintain the trust of our enterprise customers but has also positioned us to adapt to emerging security challenges as AI technology continues to evolve. The future of AI security will require even more sophisticated approaches to data protection, and we're committed to staying at the forefront of these developments.

Click here to book a demo of our award-winning AI-driven sourcing platform.

References

[1] IBM Security. "Cost of a Data Breach Report 2024." IBM Security, 2024. https://www.ibm.com/reports/data-breach

[2] Haim, N., Vardi, G., Yehudai, G., Shamir, O., & Irani, M. "Reconstructing Training Data From Trained Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) 2022. https://openreview.net/forum?id=Sxk8Bse3RKO

Our Chief Customer Officer Keith Hausmann highlights the big trends he expects to see in procurement in 2025 and as you would expect his predictions are dominated by AI and how it can help the function to operate more efficiently while driving savings and adding more strategic value:

1. The Year AI Goes Mainstream

In 2024, AI evolved from holding a Bachelor's degree to earning a PhD. Despite this, many CPOs are still sitting on the sidelines, watching peers in Marketing or Engineering dive into the AI revolution.

In 2025, this hesitation will end. The entire spectrum of AI—from LLMs to predictive analytics to autonomous agents—will become procurement’s new playground. To showcase its potential, we partnered with HFS Research to reality-check our claims about AI’s transformative power in sourcing.

What they discovered from our customers such as T. Rowe Price, Fidelity Investments and UCB Pharma surprised even us: automated spend management is delivering instant savings of 20% from more competition and transparency in the sourcing process while the technology enables business users to self-serve, allowing enterprises to competitively manage more spend, even with lower headcount.

If this is the emerging benchmark for AI in Procurement, it’s clear there’s no time left to wait. In 2025 more and more CPOs will embrace the shift to AI-driven strategies to stay competitive and drive better business outcomes.

2. From 'Should We Try AI?' to ‘How Fast Can We Start?’

For three or four years, we’ve been championing the remarkable ROI that AI delivers in sourcing. Back in 2021, we boldly predicted that for procurement to be recognized as a driver of strategic growth and enterprise value, CPOs would need to transform their operating models. This meant embracing a best-of-breed ecosystem that enables multiple digital solutions to work seamlessly together, enhancing user experience while leveraging advanced technologies to eliminate repetitive manual tasks and empower teams to focus on more meaningful, value-creating work.

Fast forward to 2025—and that vision is becoming reality. AI is elevating procurement professionals from being perceived as back-office operators to becoming consultants and trusted advisors with profound business acumen.

In that same set of predictions, we also highlighted a critical shift that’s now materializing: Procurement processes must become autonomous and self-serve whenever possible. By democratizing procurement—particularly for spend outside of procurement’s direct control—generative AI is making this transformation a reality.

Organizations we’ve been engaging with since then are now telling us that in 2025, the question is no longer if AI should be leveraged in procurement, but rather who will adopt it—and how quickly. The momentum is undeniable, building to such a degree that it’s hard to imagine any other technology dominating the conversation over the next twelve months.

3. The Next Big Thing: Agentic AI

Agentic AI has the power to completely revolutionize the field. Why? Because it promises to deliver exactly what CPOs have long been dreaming of.

When I talk to our customers about the future of [Globality’s AI Agent] Glo, I describe a scenario where they can simply ask: ‘Hey Glo— could you scan my spend portfolio and find the top three categories that have the most supplier fragmentation and recommend which 15% of my supply based could handle the majority of my spend?"’

When procurement leaders hear that, they tell me, ‘That’s my dream.’ Could 2025 be the year that dream starts to come true? Only time will tell, but my team firmly believes that Agentic AI is on the verge of making it a reality.

4. The Value of AI in Procurement is in the Billions and Counting

Early adopters of AI in procurement are delivering such significant value to their organizations that their contributions are now being highlighted in company annual reports, as has happened with BT. BT noted that '[Globality’s] generative AI features are accelerating our scoping processes and streamlining how we define our needs, while its new E-Negotiation and online NDA tools are simplifying the entire sourcing process.' Similarly, Santander has reported notable benefits, and Harold Wu, CPO at T. Rowe Price, achieved over  $40 million in operational savings—a success highlighted by the company CEO in The Financial Times’ Ignites news service. Expect more such public declarations to emerge soon.

Looking ahead to 2025 and beyond, we estimate that the augmentation of the CPO’s office with these advanced technologies will unlock substantial savings and redefine the strategic role of procurement in driving enterprise value.

5. A New Class of AI-driven CPOs Will Lead the Function

Forward-thinking Chief Procurement Officers who are stepping up to the plate to remind us of the value of the function, and what a new, AI-led, data-driven approach to it can offer are on the rise.

This isn’t solely about Globality’s customers—it’s a broader trend led by trailblazers like Paula Glickenhaus at Bristol Myers Squibb, Cyril Pourrat at BT Sourced, Charles Letizia at Tesco and Matt Prichard at Fidelity. These leaders are leveraging autonomous sourcing to revolutionize their organizations’ indirect spend strategies and embracing cutting-edge, digital-first methodologies.

There’s a palpable buzz within the profession about the new ‘rock star’ status of forward-thinking CPOs. Millennials and Gen Z business leaders are also driving this momentum, rejecting outdated, cumbersome RFx processes in favor of fast, efficient digital solutions. In 2025, we’ll see even more innovative CPOs emerging and a surge of interest from digital natives in this historically under-automated part of the business."

Click here to book a demo or here to explore more customer stories and see firsthand how AI-driven sourcing is shaping the Future of Procurement.

As the year draws to a close, it’s an ideal moment to reflect on the transformative impact of AI-driven autonomous sourcing—not only on the bottom line amid continued economic uncertainty but also on people’s lives across the globe. In 2024, organizations that embraced this next-generation technology have achieved incredible results, driving growth and efficiency while delivering tangible, life-changing benefits to individuals and communities.

Driving Speed-to-Market for New Healthcare Treatments

In 2024, Globality helped increase the speed of the clinical development cycle at a €5bn Pharma company, using the power of native-built AI to ensure novel therapies were with patients quicker, giving them new hope for conditions such as auto-immune and other rare diseases.

In healthcare, where every second counts, autonomous sourcing has enabled global life sciences companies to scale their procurement operations and uncover new opportunities. For instance, one leading life sciences organization increased the amount of spend competitively sourced by an astonishing 500%—and did so without needing to add a single new member to its procurement team. By leveraging AI, it optimized workflows, reduced manual effort, and focused on what matters most: delivering innovative solutions to patients worldwide.

Helping Families Through the Cost-of-Living Crisis

Closer to home, AI-driven sourcing is also helping consumers at a more immediate level. As the cost-of-living crisis continues to impact families across Europe, Globality’s platform has enabled one of the continent’s leading grocery retailers to maintain low prices for essential goods. By optimizing supplier selection and negotiating better terms through AI, the company ensured that families could afford a little more during the holidays—whether it’s a special meal or gifts for loved ones.

This highlights how procurement, when powered by advanced technology, extends far beyond the back office. By reducing costs and increasing efficiency, businesses can reinvest savings into keeping products affordable, supporting their customers, and delivering greater value when it’s needed most.

Transforming Procurement Operating Models

While these individual successes are powerful, the broader trend is equally transformative. Leading global enterprises have used autonomous sourcing to revolutionize their procurement operating models, empowering teams to do more with less. These organizations have proven that AI can help drive enterprise-wide growth while allowing procurement to evolve into a more strategic, value-adding function.

Consider the following examples of how top organizations are redefining procurement:

• A global life sciences company increased competitively sourced spend by 500% using the same team, demonstrating the power of AI to enhance efficiency without adding headcount.
• A Fortune 500 asset management company automated more than $400 million of spend within just two quarters, freeing up resources to focus on strategic initiatives.
• A leading market retailer leveraged autonomous negotiations to achieve $100 million in savings, unlocking value that could be reinvested elsewhere in the business.
• A top healthcare company empowered its business stakeholders to run over 1,500 sourcing projects autonomously, enabling procurement talent to focus on developing category strategies and strengthening business partnerships.

These examples underscore a critical shift: procurement is no longer just about cost-cutting. It’s about driving measurable business outcomes, increasing speed-to-market, and enhancing collaboration across the enterprise.

A Fair and Transparent Ecosystem

At Globality, our mission has always been clear: to build a fair, transparent, and innovative ecosystem for how companies do business together. In today’s fast-paced and uncertain world, this mission has never been more relevant. AI-driven autonomous sourcing is leveling the playing field, enabling organizations to operate efficiently, unlock savings, and reinvest resources into growth and innovation.

Looking ahead to 2025, we’re excited to build on this momentum and continue supporting businesses in achieving their goals. Whether it’s improving healthcare access, supporting families during economic challenges, or helping enterprises transform their operating models, the potential of autonomous sourcing is limitless.

Join Us on This Mission

The results speak for themselves: AI-driven autonomous sourcing isn’t just a technology upgrade—it’s a strategic enabler that empowers organizations to achieve more with less.

If you’d like to learn more about how Globality can help your business drive savings, streamline procurement, and make a meaningful impact, we invite you to join us on this journey.

Click here to book a demo or here to explore more customer stories and see firsthand how AI-driven sourcing is shaping the Future of Procurement.

Our Chief Customer Officer Keith Hausmann highlights the big trends he expects to see in procurement in 2025 and as you would expect his predictions are dominated by AI and how it can help the function to operate more efficiently while driving savings and adding more strategic value:

1. The Year AI Goes Mainstream

In 2024, AI evolved from holding a Bachelor's degree to earning a PhD. Despite this, many CPOs are still sitting on the sidelines, watching peers in Marketing or Engineering dive into the AI revolution.

In 2025, this hesitation will end. The entire spectrum of AI—from LLMs to predictive analytics to autonomous agents—will become procurement’s new playground. To showcase its potential, we partnered with HFS Research to reality-check our claims about AI’s transformative power in sourcing.

What they discovered from our customers such as T. Rowe Price, Fidelity Investments and UCB Pharma surprised even us: automated spend management is delivering instant savings of 20% from more competition and transparency in the sourcing process while the technology enables business users to self-serve, allowing enterprises to competitively manage more spend, even with lower headcount.

If this is the emerging benchmark for AI in Procurement, it’s clear there’s no time left to wait. In 2025 more and more CPOs will embrace the shift to AI-driven strategies to stay competitive and drive better business outcomes.

2. From 'Should We Try AI?' to ‘How Fast Can We Start?’

For three or four years, we’ve been championing the remarkable ROI that AI delivers in sourcing. Back in 2021, we boldly predicted that for procurement to be recognized as a driver of strategic growth and enterprise value, CPOs would need to transform their operating models. This meant embracing a best-of-breed ecosystem that enables multiple digital solutions to work seamlessly together, enhancing user experience while leveraging advanced technologies to eliminate repetitive manual tasks and empower teams to focus on more meaningful, value-creating work.

Fast forward to 2025—and that vision is becoming reality. AI is elevating procurement professionals from being perceived as back-office operators to becoming consultants and trusted advisors with profound business acumen.

In that same set of predictions, we also highlighted a critical shift that’s now materializing: Procurement processes must become autonomous and self-serve whenever possible. By democratizing procurement—particularly for spend outside of procurement’s direct control—generative AI is making this transformation a reality.

Organizations we’ve been engaging with since then are now telling us that in 2025, the question is no longer if AI should be leveraged in procurement, but rather who will adopt it—and how quickly. The momentum is undeniable, building to such a degree that it’s hard to imagine any other technology dominating the conversation over the next twelve months.

3. The Next Big Thing: Agentic AI

Agentic AI has the power to completely revolutionize the field. Why? Because it promises to deliver exactly what CPOs have long been dreaming of.

When I talk to our customers about the future of [Globality’s AI Agent] Glo, I describe a scenario where they can simply ask: ‘Hey Glo— could you scan my spend portfolio and find the top three categories that have the most supplier fragmentation and recommend which 15% of my supply based could handle the majority of my spend?"’

When procurement leaders hear that, they tell me, ‘That’s my dream.’ Could 2025 be the year that dream starts to come true? Only time will tell, but my team firmly believes that Agentic AI is on the verge of making it a reality.

4. The Value of AI in Procurement is in the Billions and Counting

Early adopters of AI in procurement are delivering such significant value to their organizations that their contributions are now being highlighted in company annual reports, as has happened with BT. BT noted that '[Globality’s] generative AI features are accelerating our scoping processes and streamlining how we define our needs, while its new E-Negotiation and online NDA tools are simplifying the entire sourcing process.' Similarly, Santander has reported notable benefits, and Harold Wu, CPO at T. Rowe Price, achieved over  $40 million in operational savings—a success highlighted by the company CEO in The Financial Times’ Ignites news service. Expect more such public declarations to emerge soon.

Looking ahead to 2025 and beyond, we estimate that the augmentation of the CPO’s office with these advanced technologies will unlock substantial savings and redefine the strategic role of procurement in driving enterprise value.

5. A New Class of AI-driven CPOs Will Lead the Function

Forward-thinking Chief Procurement Officers who are stepping up to the plate to remind us of the value of the function, and what a new, AI-led, data-driven approach to it can offer are on the rise.

This isn’t solely about Globality’s customers—it’s a broader trend led by trailblazers like Paula Glickenhaus at Bristol Myers Squibb, Cyril Pourrat at BT Sourced, Charles Letizia at Tesco and Matt Prichard at Fidelity. These leaders are leveraging autonomous sourcing to revolutionize their organizations’ indirect spend strategies and embracing cutting-edge, digital-first methodologies.

There’s a palpable buzz within the profession about the new ‘rock star’ status of forward-thinking CPOs. Millennials and Gen Z business leaders are also driving this momentum, rejecting outdated, cumbersome RFx processes in favor of fast, efficient digital solutions. In 2025, we’ll see even more innovative CPOs emerging and a surge of interest from digital natives in this historically under-automated part of the business."

Click here to book a demo or here to explore more customer stories and see firsthand how AI-driven sourcing is shaping the Future of Procurement.

As the year draws to a close, it’s an ideal moment to reflect on the transformative impact of AI-driven autonomous sourcing—not only on the bottom line amid continued economic uncertainty but also on people’s lives across the globe. In 2024, organizations that embraced this next-generation technology have achieved incredible results, driving growth and efficiency while delivering tangible, life-changing benefits to individuals and communities.

Driving Speed-to-Market for New Healthcare Treatments

In 2024, Globality helped increase the speed of the clinical development cycle at a €5bn Pharma company, using the power of native-built AI to ensure novel therapies were with patients quicker, giving them new hope for conditions such as auto-immune and other rare diseases.

In healthcare, where every second counts, autonomous sourcing has enabled global life sciences companies to scale their procurement operations and uncover new opportunities. For instance, one leading life sciences organization increased the amount of spend competitively sourced by an astonishing 500%—and did so without needing to add a single new member to its procurement team. By leveraging AI, it optimized workflows, reduced manual effort, and focused on what matters most: delivering innovative solutions to patients worldwide.

Helping Families Through the Cost-of-Living Crisis

Closer to home, AI-driven sourcing is also helping consumers at a more immediate level. As the cost-of-living crisis continues to impact families across Europe, Globality’s platform has enabled one of the continent’s leading grocery retailers to maintain low prices for essential goods. By optimizing supplier selection and negotiating better terms through AI, the company ensured that families could afford a little more during the holidays—whether it’s a special meal or gifts for loved ones.

This highlights how procurement, when powered by advanced technology, extends far beyond the back office. By reducing costs and increasing efficiency, businesses can reinvest savings into keeping products affordable, supporting their customers, and delivering greater value when it’s needed most.

Transforming Procurement Operating Models

While these individual successes are powerful, the broader trend is equally transformative. Leading global enterprises have used autonomous sourcing to revolutionize their procurement operating models, empowering teams to do more with less. These organizations have proven that AI can help drive enterprise-wide growth while allowing procurement to evolve into a more strategic, value-adding function.

Consider the following examples of how top organizations are redefining procurement:

• A global life sciences company increased competitively sourced spend by 500% using the same team, demonstrating the power of AI to enhance efficiency without adding headcount.
• A Fortune 500 asset management company automated more than $400 million of spend within just two quarters, freeing up resources to focus on strategic initiatives.
• A leading market retailer leveraged autonomous negotiations to achieve $100 million in savings, unlocking value that could be reinvested elsewhere in the business.
• A top healthcare company empowered its business stakeholders to run over 1,500 sourcing projects autonomously, enabling procurement talent to focus on developing category strategies and strengthening business partnerships.

These examples underscore a critical shift: procurement is no longer just about cost-cutting. It’s about driving measurable business outcomes, increasing speed-to-market, and enhancing collaboration across the enterprise.

A Fair and Transparent Ecosystem

At Globality, our mission has always been clear: to build a fair, transparent, and innovative ecosystem for how companies do business together. In today’s fast-paced and uncertain world, this mission has never been more relevant. AI-driven autonomous sourcing is leveling the playing field, enabling organizations to operate efficiently, unlock savings, and reinvest resources into growth and innovation.

Looking ahead to 2025, we’re excited to build on this momentum and continue supporting businesses in achieving their goals. Whether it’s improving healthcare access, supporting families during economic challenges, or helping enterprises transform their operating models, the potential of autonomous sourcing is limitless.

Join Us on This Mission

The results speak for themselves: AI-driven autonomous sourcing isn’t just a technology upgrade—it’s a strategic enabler that empowers organizations to achieve more with less.

If you’d like to learn more about how Globality can help your business drive savings, streamline procurement, and make a meaningful impact, we invite you to join us on this journey.

Click here to book a demo or here to explore more customer stories and see firsthand how AI-driven sourcing is shaping the Future of Procurement.

AI has been democratized so quickly, already used in so many areas of our lives (it's the only tech that both my parents and my kids adopted at the same time, but that's a story for another day!). It's also become a commodity. GenAI is everywhere these days - from search engines to mobile phone software to music composition tools.

However, just because GenAI is everywhere, doesn’t necessarily mean it’s always welcome, or indeed working well, everywhere. Corporate procurement is a notable exception. Procurement is unique because it’s a complex, intensive process whose decisions not only impact the bottom line but can also determine success. Enhancing procurement with AI helps companies identify their best-fit suppliers, even in historically hard-to-procure spend areas that are complex and high-value. Because these areas have also been the hardest for machines to understand, they’ve been the most challenging to automate and optimize, relying exclusively on humans to handle.

At last, that’s changing. Procurement specialists no longer need to spend hours or days writing long, detailed briefs that cover every possible sourcing scenario. Now, they can “partner” with an AI agent, trained over many years by procurement experts, to receive a personalized sourcing journey with instant access to all the information and insights they need.

This is game-changing. No matter the company, bidding for complex services requires teams to articulate their needs through lengthy RFPs. The complexity and detail of these documents make it difficult to fairly and accurately evaluate and compare vendors' solutions, proposals, pricing, and specific requirements such as diversity, sustainability, and cultural fit. 

Using AI Agents to Increase Your Impact Across the Business

Doing this work repeatedly, at scale, is a big ask for procurement teams. That’s why being able to actually “converse” about every aspect of a brief with systems that have infinite amounts of patience, vast recall, and meticulous attention to detail is a real step change. Effectively these systems act as informed colleagues who read all the information for you, synthesizing them in seconds to give fast answers, and generating ideal responses to the market that are compliant with all your company policies.

Procurement teams can now convey “complex intent” at different stages of the buying journey, using AI to extract project information from existing documents and performing scoping interviews using natural, conversational language. This enables them to define what they need quickly and easily to avoid overbuying, manage demand, and save time on every sourcing event.

Adobe's Chief Strategy Officer and closely followed AI trend watcher Scott Belsky has been writing about how AI agents will streamline and optimize operating models to increase efficiencies and productivity.

As he writes, “Rather than hire out teams of specialists for every function, companies will have the opportunity to purchase AI capabilities—often in the form of agent-based tools or ‘AI teammates’—that (or is it who?) automate parts of a process or entire workflows within individual functions.”

Having such a partner not only saves considerable time but also helps business users achieve much better outcomes than trying to do all this on their own. Why? Because dedicated AI-teammates such as Globality’s agent Glo, built from the ground up for nearly a decade, can draw on massive bodies of accumulated knowledge and intelligence from millions of buyer and seller transactions.

Crucially, the ultimate decision-making remains with the carbon and not silicon-based side of the partnership. Whether or not we are truly heading for Gartner’s vision of a world where machines increasingly buy from machines, and where, by as soon as 2030, 15-20% of your revenue will come from selling directly to such non-human customers, I believe a large part of B2B procurement will increasingly be driven and orchestrated by human experts working in productive partnerships with AI agents.

Adopt the Power AI to Reap the Benefits

By partnering with this new class of AI agents, buyers will not only work smarter, but they’ll also enhance their reputation across the enterprise. Implementing data-driven processes that identify the best providers, proposals, and outcomes will lead to improved business metrics, enabling procurement to add more strategic value and help drive new growth. As the effectiveness of these processes becomes more visible, increasing numbers of stakeholders, including those who typically avoid procurement, will become engaged, bringing more spend under management.

However, it’s important to emphasize that unlike other areas, in complex sourcing we’re not yet talking about machine-to-machine-only transactions. Complex purchasing decisions always involve relationships; buyers and sellers need to feel confident and trust each other. Partnering with AI automates low-value repetitive, manual tasks, allowing you to focus on more strategic work such as supplier collaboration, scenario planning and becoming a true partner to the business. Relationships (internal and external) will always be crucial in procurement, and these will continue to be managed and led by people, while AI agents do the background work.

Be Bold and Stand Out From the Crowd

So, my advice to procurement professionals is this: just as you continually develop and nurture your partnerships with colleagues, focus on how to best partner with AI. Consider the types of guidance, instructions, and prompts you can develop to unleash AI’s potential within your organization. Strive to create an impact that is unparalleled and uniquely tailored to you, your company, your creativity, and your proprietary data.

This approach is both the most creative and value-adding strategy you can adopt for using AI agents to help better manage all your company spend, as well as for your personal career development, marking you out as a forward-thinking procurement leader who wants to move the profession from tactical back-office function to strategic driver of growth at heart of the business.

Click here to learn more about how Globality's AI-driven autonomous sourcing platform automates routine tasks and enables procurement teams to focus on more strategic tasks

The statistics tell an alarming story: according to IBM's 2024 Cost of a Data Breach Report [1], the average cost of a data breach has now reached $4.88 million. The report highlights an emerging concern: attackers are increasingly leveraging AI and automation tools, adding complexity to the threat landscape and extending breach lifecycles by weeks or months.

But beyond these numbers lies a more nuanced reality; as AI transforms business processes, it creates novel attack surfaces and security challenges that traditional frameworks struggle to address. The rapid adoption of AI technologies across industries has fundamentally changed the security landscape, introducing complexities that weren't even contemplated in traditional security frameworks. Organizations now face the dual challenge of protecting not just their data, but also the AI models that process it, the training data that shapes these models, and the outputs they generate.

At Globality, we've learned that robust security isn't just about checking boxes; it's about building a comprehensive shield around customer data that evolves with emerging threats. While we're proud of our ISO 27001 certification and SOC2 compliance (both recently reaffirmed through rigorous audits), we see these as foundations rather than finish lines. These certifications represent our commitment to maintaining rigorous security standards, but our actual security practices go well beyond what these frameworks require. We've built our security infrastructure with the understanding that in today's landscape, compliance is merely the starting point.

Beyond Standards: Security in Practice

The rise of AI has introduced new complexities in data protection that few organizations are fully prepared to address. Traditional security models often fall short when confronted with the unique challenges of AI systems.

Data residency requirements have become increasingly complex, varying not just by country, but by data type and processing stage. Organizations must now track and control data flows across multiple jurisdictions, ensuring compliance with a patchwork of regulations while maintaining system performance. This becomes particularly challenging when AI models need to process data across borders or when training data comes from multiple jurisdictions.

The protection of both training data and model outputs presents another layer of complexity. At Globality, we've developed sophisticated approaches to this challenge. Our AI models fall into two main categories; classifiers for categorizing projects based on natural language descriptions, and clustering/ranking models for provider matching. Each requires its own careful security consideration. For classifier training, we've implemented a rigorous four-step anonymization and sanitization pipeline:

• We systematically remove client-specific identifiers and codes
• We employ Named Entity Recognition (NER) to identify and remove personal and company proprietary information
• We use sophisticated techniques like Normalized Google Distance (NGD) calculations to identify and redact client-specific entities
• We implement reproducible name mangling for sensitive terms

This process, performed with heavy involvement by Globality InfoSec personnel, ensures that while our models can learn from aggregate patterns, they never retain or expose sensitive client information. We're particularly stringent about personal identifiable information (PII); it's completely excluded from our training pipeline.

For our clustering and ranking models, which process a wide array of supplier data, we've implemented strict controls on data sourcing and usage. While we collect data from public, private, and proprietary sources, we maintain clear boundaries around what data can be used for model training. We've explicitly designed our systems to exclude sensitive proprietary data from model training without explicit customer consultation and approval.

Ensuring AI systems maintain security during both training and inference requires a comprehensive approach that traditional security frameworks don't fully address. During training, we must protect against data poisoning attacks and unauthorized access to training data. During inference, we need to guard against model extraction attacks and ensure that model outputs don't leak sensitive information.

To address these challenges, we've implemented advanced security measures that go beyond standard practices. For example, our Hold Your Own Key (HYOK) encryption capability gives customers complete control over their data while maintaining functionality, and our AI Governance Committee provides oversight of all AI changes from model improvements to prompt evaluation.

IP allowlisting is another critical component of our security infrastructure that we've implemented as part of a broader zero-trust architecture to protect every point of ingress (including both web application and REST API requests). This means every access attempt, whether from an allowed IP or not, undergoes rigorous authentication and authorization checks. We've also adopted the ISO 42001 framework for AI systems, ensuring security is built into our AI operations from the ground up, not bolted on as an afterthought.

Practical Security Advice for the AI Era

Based on our experience protecting sensitive enterprise data, we've developed a comprehensive set of security principles that organizations should consider as they build out their AI infrastructure:

• Treat AI model inputs and outputs with the same rigorous security controls as your raw data. Many organizations focus on securing their databases but leave model interactions inadequately protected. This creates vulnerabilities that sophisticated attackers can exploit. Recent research has demonstrated how seemingly innocuous model outputs can potentially be used to reconstruct training data [2]. That's why we've implemented end-to-end encryption for all model interactions, ensuring that data remains protected at every stage of processing.
• Implement granular access controls as part of a comprehensive zero-trust architecture. IP allowlisting is just the beginning; every access request should be validated regardless of its source. This means implementing strong authentication mechanisms, regular access reviews, and detailed audit logging. At Globality, we maintain comprehensive audit trails of all system access, enabling us to detect and respond to potential security incidents quickly.
• Encryption should be end-to-end, with customer control over keys. Our HYOK implementation demonstrates that robust encryption doesn't have to come at the cost of functionality. We've developed sophisticated key management systems that allow customers to maintain complete control over their data while still leveraging our AI capabilities. This includes automatic key rotation, secure key storage, and immediate revocation capabilities.
• Implement comprehensive data anonymization pipelines for AI training. This isn't just about removing obvious identifiers; it requires a sophisticated multi-layer approach that considers context and relationships between data points. Our experience shows that effective anonymization must combine rule-based systems, machine learning techniques, and careful human oversight.
• Embrace data minimization as a fundamental security principle. At Globality, we rigorously define what data we need and only use the data required. We also carefully select our models and vendors, and we don't allow third parties to use any data we send through their APIs for AI training. This approach follows a core security principle: the best way to mitigate risk is to minimize the data you hold in the first place. By being intentional about data collection and processing, organizations can significantly reduce their attack surface and potential exposure.

The Path Forward

The reality is that security in the AI era requires a fundamental shift in how we think about data protection. It's not enough to secure static data; we need to protect information as it flows through increasingly complex AI systems. This means implementing security controls that understand and account for the unique characteristics of AI workflows, from data ingestion through model training and inference.

Our commitment to security at Globality goes beyond maintaining certifications and implementing standard security measures. We're continuously evolving our security infrastructure to address emerging threats and protect our customers' data in an increasingly complex technological landscape. By sharing our experiences and insights, we hope to contribute to the development of more robust security practices across the industry.

This approach has not only helped us maintain the trust of our enterprise customers but has also positioned us to adapt to emerging security challenges as AI technology continues to evolve. The future of AI security will require even more sophisticated approaches to data protection, and we're committed to staying at the forefront of these developments.

Click here to book a demo of our award-winning AI-driven sourcing platform.

References

[1] IBM Security. "Cost of a Data Breach Report 2024." IBM Security, 2024. https://www.ibm.com/reports/data-breach

[2] Haim, N., Vardi, G., Yehudai, G., Shamir, O., & Irani, M. "Reconstructing Training Data From Trained Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) 2022. https://openreview.net/forum?id=Sxk8Bse3RKO

When you think of procurement, the first association is not necessarily ‘cool’. But here’s a radical thought: AI is making procurement one of the coolest functions in the enterprise! I previously led an AI development team at Microsoft’s Xbox, so I know what cool tech is, and I passionately believe that procurement + AI is not only cool, it is, in fact, glamorous and the cutting-edge of every global corporation.

First, we need to agree with the premise that ‘cool’ is a function of creativity, innovation, impact, personal brand and, as my Globality co-founder Joel Hyatt argued in a recent Forbes article, purpose. AI is enhancing all of these attributes across procurement and helping transform the function into a place where the brightest and best want to make their mark.

There’s a very serious point here in the context of the current skills shortage. A recent Gartner study found that only one in six procurement teams believe they have “adequate talent” to meet their future needs. Companies seeking to recruit the best talent and use procurement strategically must have an edge – and that edge is AI. 

So, let’s break down those cool factors: 

Creativity – Fairly or unfairly, procurement’s image is tainted by its association with box-ticking. When many people think of procurement, they think of compliance, regulations, and bureaucracy. This necessary emphasis on processes and controls can give the impression that procurement lacks creativity or flexibility. The good news is that democratizing data access and handling routine processes is exactly what AI does most efficiently, freeing up procurement people to be more imaginative and creative. 

That creativity will look different in every company. It might focus on driving sustainable and ethical practices that positively impact the brand, society, and the environment. Or it could involve collaborating more closely with various departments, suppliers, and other stakeholders. Or running campaigns to raise awareness internally and externally to promote the ways that procurement is having a positive impact through measures like cost savings, risk management, innovation, and sustainability. Or simply staying on top of market trends and being more strategic. 

Innovation – Using AI-driven technology is innovative by definition. However, procurement stands out as one of the best corporate use cases for Gen AI in particular. Gen AI in procurement can analyze and synthesize huge volumes of complex, unstructured text-based documents to help specialists in all types of sourcing scenarios – from scoping RFPs to making buying decisions. 

The key here is learning to “partner” with AI. Complex, high-stakes spend categories are the most difficult to procure – and until now, to automate. Today, instead of investing hours or days writing a long, detailed brief that covers every possible scenario, anyone can “converse” with Gen AI. They can convey what we call “complex intent” at different stages in the procurement journey using natural language. This not only saves considerable time but achieves much better outcomes because the AI is drawing on a massive body of accumulated knowledge and intelligence from huge number of buyer and seller transactions. 

The bottom line here is that AI-powered innovation is doing much more than simply automating simple procurement tasks. It’s transforming a complex process that has never been humanly possible to do efficiently, optimally, and personally, with a realistically sized team of procurement specialists. 

Impact – What’s cooler in today’s lean, cost-conscious business climate than being able to make a positive impact on productivity? As Scott Belsky, Adobe’s Chief Product Officer and board member of Globality, says in his Substack Implications: “As smaller companies modernize using a new AI-native stack of technology, they no longer need to grow their team to scale their ambition.” 

Procurement’s reputation has suffered in the past due to productivity issues. Activities like data entry, invoice processing, and purchase order processing were very manual and error prone. Systems were fragmented and siloed, leading to inefficiencies. Supplier management was inconsistent and unstructured. AI-based procurement addresses all these issues. 

Of course, the other huge impact of AI-based procurement is its ability to source more intelligently and save companies huge amounts of money. Matt Prichard, Fidelity Investments’ CPO, reported seeing a 20% price improvement by using AI-based autonomous sourcing, for example. 

Personal Brand – The inherent stress of working in procurement with its complexity, tight deadlines, and cost targets makes work difficult enough. But the negative stereotypes about procurement as an obstacle to ‘get around,’ which causes friction and complications, can feel demoralizing. 

Procurement people I’ve met genuinely want to make a positive difference in their companies. But if specialists lack the tools and technology to do their jobs productively, at the pace of business, they are set up to fail, which grinds down morale. 

By liberating people from the drudgery in procurement, making every step of the journey faster, and delivering better outcomes, AI improves every aspect of the function and the lives of those who deliver it. 

To conclude, it is worth reiterating that procurement drives the trade of trillions of dollars around the world. With the power of AI-driven sourcing technology, procurement teams will be participating in the creation of the largest economic engine of our lives, something which glues the world together. I think we can all agree that’s pretty cool!

As the buzz around AI, and gen AI in particular, refuses to die down all CFOs are on the hook from their CEOs and boards to find use cases for this game-changing technology that deliver instant upticks in productivity and efficiencies while reducing OpEx and positively impacting the bottom line. A select group of innovators have identified that procurement is the lowest-hanging fruit out there, enabling enterprises to drive more value from their company spend by implementing enterprise-wise procurement mandates.

They are adopting AI-driven sourcing and spend management technology to ensure that all third-party spend is tendered fairly, competitively, and transparently — with the right guardrails and policies in place to maintain compliance and risk management. As a result, these CFOs are instantly able to get more visibility, control and assurance of buying the right goods and services at fair market prices across all of their expenditures.

Global 2000 companies spend billions of dollars each year but legacy procurement processes and technology mean that many employees simply bypass the designated systems and engage in ‘maverick’ or ‘rogue’ spend as they need to be able to execute their jobs in the marketing, R&D, technology, human resources, real-estate and other functions in the company with a reasonable degree of speed and simplicity.

But forward-thinking finance leaders have identified autonomous sourcing as the answer to this conundrum – the user-friendly, consumer-like experience means using this technology for all company spend above a certain threshold is one mandate that their workforce is happy to embrace.

Let’s look at what CFOs need to consider in order to encourage participation in the process and make sure procurement mandates drive their companies toward the goal of delivering savings, reduced operating expenses and improved business results.

Why more companies are choosing mandates
Traditionally, mandates haven’t always been welcomed by employees, particularly those within the “frozen middle” of organizations where there’s a large disconnect between the declared company strategy and operational imperatives and ultimately the execution by mid-level managers. However, employees will often take the path of least resistance and not follow recommended business processes and practices as they know there are no consequences for doing so, as long as they don’t exceed their budget. While this ensures budgets are not surpassed, it also ensures companies WILL get less for more within that budget. 

With mandates, CFOs can quickly and effectively encourage the behaviors needed to deliver on business goals, principally more efficient cost control and adding strategic value. That’s why we’re seeing more enterprises adopt this strategy.

CFOs are also realizing that being nimble and being buttoned up are not mutually exclusive. In fact, mandates can increase efficiency and agility, especially within procurement where improved spend management directly impacts the bottom line.

Making it easy for employees to comply
For mandates to succeed, they need to be easy for every employee to comply with. It’s straightforward enough to create mandates that are clear and reasonable, such as: “Anyone spending more than a specific dollar amount on a service must participate in the procurement process.” What’s more critical is ensuring the underlying processes for the protocol you’re mandating are easy to use.

If employees are using outdated procurement systems that are difficult or cumbersome, then they’re going to struggle to comply. If you empower people with self-serve, intuitive AI-powered technology, it will make them want to use the mandated platform on an ongoing basis.

Take travel booking, for example, which used to be an agent-based travel management function. Once employees were empowered with the technology to compare rates, flight times, routes and seats, they could pick the best option that worked for them and for the company. This same model applies for CFOs looking to implement procurement mandates for all of their external spending. By giving employees user-friendly, digital solutions with a modest set of guardrails, you’ll empower them to be their own buyer and simplify compliance.

Autonomous sourcing technology enables CFOs to set mandates without having to fear the reverberation of noise – complaints that it’s too hard to comply or business stakeholders continuing to work in their old, archaic way of email and spreadsheets before going into the system right at the end of the process simply for compliance purposes. While democratizing how an organization buys everything it needs – putting the purchasing decisions in the hands of the experts who own the budgets and allowing them to work however they want – this new model ensures issues such as risk management and ESG targets are adhered to while also improving the bottom line.

Procurement mandates deliver instant cost savings
Successful implementation of a buying mandate means substantially more company spend will be managed by technology with new efficiencies and competition across a transparent, inclusive sourcing process that drives your costs 10-20% lower from day one. This fundamentally leads to either more for less, improvement to the company’s bottom-line (and therefore employee bonuses and shareholder returns) or conscious reinvestment in critical growth initiatives.

CFOs who invest in AI-driven sourcing and spend management solutions will find that mandating their use by the business is far easier than has often been the case in the past and that their organizations will both enjoy value from day one and be better positioned to manage the bottom line in the long term.

Click here to request a demo of the market leading automated spend management platform for instant improvements to your bottom line.