The Decisions That Shape Every AI Implementation

Executive Summary

Artificial intelligence is rapidly becoming embedded within the products and services organisations procure. Whether adopting enterprise AI platforms, specialised software, cloud services or industry-specific applications, organisations are increasingly making decisions that will shape how artificial intelligence influences their operations for many years to come. These decisions are often approached as procurement exercises concerned primarily with functionality, pricing and implementation timelines.

This perspective is incomplete.

The selection of an AI vendor is one of the earliest and most significant governance decisions an organisation will make. Long before a system is implemented, procurement determines where organisational data will reside, how information will be managed, what commercial dependencies will emerge and how future capability will develop. It establishes relationships that frequently extend well beyond the life of the initial contract and influences the organisation’s ability to respond to technological, regulatory and strategic change.

This paper argues that AI procurement should therefore be understood not as an administrative or technical activity, but as the first practical expression of AI governance. Effective procurement considers not only what a technology can do today, but also how vendor relationships, organisational capability and governance arrangements will shape institutional resilience over time.

For regional organisations, these decisions carry additional significance. Procurement choices influence the development of local capability, the resilience of regional institutions and the confidence with which organisations can adopt emerging technologies. Viewed through this broader lens, responsible procurement becomes an investment not only in technology, but in the future capability of both the organisation and the region it serves.

Introduction

The BRAIN Governance Insights Series has consistently argued that successful AI adoption depends less on the technology an organisation selects than on the quality of the governance surrounding it. Governance provides the structures, accountability and strategic direction that enable organisations to adopt artificial intelligence with confidence and purpose.

This paper examines where those governance principles first become operational.

For many organisations, the earliest significant AI decision is not the publication of a governance framework or the approval of a new policy. It is the decision to procure an AI-enabled product, engage a technology partner or establish a long-term relationship with a software vendor. Although these decisions are often viewed primarily through commercial or operational lenses, they establish the foundations upon which future governance will depend.

Selecting an AI vendor shapes far more than the technology an organisation acquires. It influences the relationships on which future capability will depend, the commercial and technical constraints the organisation accepts, and the degree of flexibility it retains as artificial intelligence continues to evolve. In many respects, the governance outcomes an organisation seeks during implementation have already been influenced by decisions made during procurement.

Procurement is the first practical act of AI governance. Rather than viewing procurement as an administrative process concerned primarily with price and functionality, organisations should recognise it as an opportunity to make deliberate decisions about stewardship, capability and long-term resilience. The technologies an organisation adopts will inevitably change over time. The quality of the procurement decisions that shape those technologies may endure for many years.

Procurement Is the First Practical Act of AI Governance

Procurement has traditionally been viewed as a commercial function. Organisations identify a need, evaluate available solutions and select the product or service that best meets their operational and financial requirements. While governance may influence this process through delegated authorities or approval frameworks, procurement itself has often been regarded as an administrative activity rather than a strategic one.

Artificial intelligence challenges this distinction.

Unlike many technology purchases, AI procurement establishes relationships that extend beyond the acquisition of software. It influences how decisions are supported, how information is processed, how organisational knowledge is retained and how future capabilities evolve. The technologies selected today will continue to change through new models, updated features and evolving commercial arrangements, meaning the governance implications of procurement persist long after a contract has been signed.

This changes the nature of procurement itself.

Selecting an AI vendor is not simply a decision about functionality or price. It is a decision about which organisation will become embedded within the institution’s future operating model. Every procurement decision allocates responsibility, creates dependency and establishes expectations regarding transparency, accountability and stewardship. These are governance considerations before they are procurement considerations.

Recognising procurement as governance encourages organisations to broaden the questions they ask before committing to a technology. Rather than focusing solely on product capability, leaders should also consider the long-term relationship they are establishing, the organisational capability they are developing and the governance responsibilities they are accepting. Technical evaluation remains important, but it should sit alongside a broader assessment of strategic fit, institutional resilience and the organisation’s ability to adapt as artificial intelligence continues to evolve.

Governance does not begin when an AI system is deployed into the workplace. It begins when an organisation decides who it will trust to help shape its future capability. Procurement is therefore not merely the first step in implementation, it is the first practical expression of AI governance.

AI Vendors Become Long-Term Strategic Partners

Most technology procurement has historically been centred on acquiring products. Organisations evaluated functionality, negotiated commercial terms and implemented solutions that remained relatively stable throughout their operational life. Although software was updated periodically, the relationship between purchaser and vendor was often transactional, with governance focused primarily on contract management and service delivery.

Artificial intelligence changes this dynamic.

Modern AI platforms evolve continuously. New foundation models are released, capabilities expand, pricing structures change and product roadmaps adapt in response to technological advances and competitive pressures. Organisations are no longer procuring static software; they are entering relationships with vendors whose decisions will continue to influence organisational capability long after procurement has concluded.

When an organisation adopts an AI platform, it also adopts the vendor’s pace of innovation, approach to security, product priorities and long-term commercial direction. Decisions made by the vendor, such as introducing new functionality, retiring existing features or altering licensing arrangements, can have direct operational and governance implications for every organisation that relies upon the platform.

Governance therefore extends beyond selecting the most capable technology available today. It requires leaders to consider whether a prospective vendor demonstrates the transparency, stability and strategic alignment necessary to support the organisation over time. The strength of an AI partnership should be assessed not only by the quality of the product, but also by the quality of the relationship it enables.

Successful procurement recognises that AI vendors become participants in an organisation’s operating model rather than simply suppliers of technology. Choosing those relationships carefully is therefore a governance decision with consequences that may endure far longer than the technology itself.

Data Stewardship Extends Beyond Data Residency

As artificial intelligence has become more widely adopted, organisations have placed increasing emphasis on understanding where their data is stored and how it is protected. Questions relating to data residency, cybersecurity and regulatory compliance have become standard components of procurement processes, reflecting the importance of safeguarding sensitive information.

These considerations remain essential, but they represent only part of the governance challenge.

Artificial intelligence systems do more than store organisational data. They interact with documents, analyse workflows, generate content and support decision-making. Through these interactions, AI systems gain insight into how an organisation operates, the language it uses, the problems it seeks to solve and the information that underpins its day-to-day activities. Procurement decisions should therefore consider not only where information resides, but also how organisational knowledge is accessed, processed and governed throughout the relationship with a vendor.

This requires organisations to ask broader governance questions. What information is retained beyond an individual interaction? How are prompts, usage patterns and metadata managed? Under what circumstances might organisational information contribute to future product development or service improvement? What contractual commitments exist regarding data handling, retention and deletion? These questions are often more consequential than data residency alone because they relate directly to stewardship, transparency and organisational trust.

Effective governance recognises that information is more than a technical asset. It is an institutional asset that reflects an organisation’s expertise, relationships and accumulated knowledge. Protecting that asset requires leaders to understand not only where information is stored, but also how it is used, who can derive value from it and what governance mechanisms exist to ensure it remains aligned with the organisation’s interests.

Responsible AI procurement therefore extends beyond compliance with technical or regulatory requirements. It requires organisations to exercise informed stewardship over the information and knowledge that underpin their future capability, ensuring that trust is maintained throughout the entire lifecycle of the vendor relationship.

Procurement Decisions Shape Regional Capability

Every organisation procures technology independently, yet the collective effect of those decisions extends well beyond individual institutions. Across a region, procurement choices influence the capabilities that are developed, the expertise that is retained and the relationships that underpin long-term economic resilience.

While procurement is often evaluated through the lens of organisational outcomes, it also contributes to the capability of the broader ecosystem in which those organisations operate. This perspective is particularly relevant for regional communities. Regional organisations frequently share workforce, suppliers, educational institutions and professional networks. 

Experience gained through one AI implementation often informs the next, creating opportunities for knowledge transfer and collaboration that are less visible when procurement is considered in isolation. Conversely, repeated procurement decisions that overlook capability development can leave organisations facing similar governance challenges independently, limiting the region’s ability to mature collectively.

This does not imply that organisations should prioritise local suppliers over better alternatives or make procurement decisions based on geography alone. Responsible procurement remains grounded in organisational needs, value for money and effective governance. However, organisations should recognise that procurement decisions can either contribute to, or diminish, the capability of the wider regional ecosystem. Sharing lessons, developing internal expertise and participating in collaborative governance initiatives all strengthen the environment in which future procurement decisions will be made.

For regional leaders, this presents an opportunity to view procurement as more than an organisational function. It becomes one of the mechanisms through which regions build institutional capability, strengthen professional networks and improve their collective capacity to adopt artificial intelligence responsibly. Over time, the quality of a region’s AI ecosystem will be shaped not only by the technologies its organisations procure, but by the governance capability those procurement decisions leave behind.

Conclusion

Artificial intelligence is changing how organisations think about technology procurement. Increasingly, procurement decisions establish the relationships, capabilities and governance arrangements that will influence an organisation long after implementation has concluded. As AI systems continue to evolve, the quality of these early decisions will become increasingly important.

This paper has argued that procurement should therefore be understood as the first practical act of AI governance. Before policies are tested, frameworks are applied or systems are deployed, organisations have already made decisions about who they will trust, what capabilities they intend to build and how they will balance opportunity with stewardship. These are governance decisions in their own right.

Viewed in this way, procurement becomes more than a process for acquiring technology. It becomes an opportunity to shape an organisation’s future operating model, strengthen institutional capability and establish the conditions for responsible innovation. The technologies an organisation adopts will inevitably evolve. The governance principles that guide procurement should remain considerably more enduring.

For leaders, the challenge is therefore not simply to procure artificial intelligence responsibly, but to recognise that every procurement decision is also a decision about the kind of organisation they are building. Organisations that approach procurement through this broader governance lens will be better positioned to adapt, maintain trust and realise the long-term benefits of artificial intelligence in an increasingly dynamic environment.

About BRAIN

The Ballarat Region Artificial Intelligence Network (BRAIN) is an independent regional institution dedicated to helping organisations and communities build the capability required to prosper in the age of artificial intelligence.

BRAIN brings together leaders from business, government, education and the community to strengthen AI capability through research, governance, education and collaboration. Its work focuses on ensuring regional communities are equipped not only to adopt artificial intelligence, but to govern it responsibly and realise its long-term economic and social benefits.

The BRAIN Governance Insights Series forms part of this broader mission, providing practical, evidence-informed guidance for leaders navigating the opportunities and challenges of AI adoption.

About the Author

Matt Bowd is Co-Founder and Chief Executive Officer of the Ballarat Region Artificial Intelligence Network (BRAIN). Through his work, he focuses on the governance, institutional and regional implications of artificial intelligence, with a particular interest in helping regional communities build the capability required to thrive in an AI-enabled economy.

Next in the Series

Paper #6 – Leading Institutions in the Age of Artificial Intelligence

Successful AI adoption requires more than governance frameworks and responsible procurement. It also demands leadership capable of guiding organisations through sustained technological, organisational and societal change.

The next paper in the BRAIN Governance Insights Series explores how boards, executives and institutional leaders can build organisations that remain adaptable, trusted and resilient as artificial intelligence continues to reshape the environments in which they operate.