Future-Proofing with AI and Automation Governance
AI and automation have become significant drivers of technological and business transformation. The global market size for artificial intelligence was approximately $150.2 billion in 2023 and is projected to grow to an astounding $1,345.2 billion by 2030, This growth is fueled by advancements in machine learning, natural language processing, and the integration of AI across all industries.
For automation specifically, the global market was valued at about $225 billion in 2022, and its expansion is closely tied to the adoption of AI-driven solutions, including robotic process automation (RPA), intelligent workflows, and self-service technologies
The rapid adoption of AI and automation reflects their ability to reduce costs, enhance efficiency, and deliver real-time insights. In IT service management (ITSM), they are pivotal for streamlining tasks like incident management, predictive maintenance, and customer service enhancement, which helps organisations reduce operational burdens while improving user experiences.
➡️ What’s Driving the Need for AI and Automation Governance?
The Rise of AI and Automation: By 2025, AI and automation will play an increasingly critical role in IT Service Management (ITSM) and broader business operations. These technologies have the potential to streamline workflows, enhance decision-making, and drive innovation. However, without a structured governance framework, organisations risk chasing opportunities that don't align with their goals, wasting resources, or failing to achieve meaningful outcomes. Governance ensures that AI and automation initiatives are both strategic and impactful.
Managing Demand in Alignment with Business Needs: With AI and automation solutions advancing rapidly, technology leaders often face a flood of new requests. A governance framework helps organisations adopt a structured approach to manage demand, ensuring that resources are focused on projects that align with business objectives. By prioritising initiatives that deliver measurable value, organisations avoid the inefficiencies of misdirected investments and ensure alignment with long-term goals.
Avoiding "Shiny Penny Syndrome": Technology vendors frequently showcase cutting-edge AI and automation features, creating pressure to adopt the latest innovations. However, not all advancements are relevant to every organisation. A governance process provides a clear and objective method to assess, prioritise, and validate new capabilities, ensuring that they fit within strategic priorities and avoid the pitfalls of chasing trends that lack organisational relevance.
Strengthening Business Relationships and Driving Investment Decisions: Governance frameworks create a foundation for stronger collaboration between IT and business stakeholders. By involving all parties in the evaluation and decision-making process, organisations build trust and alignment on priorities. This approach not only fosters stronger relationships but also helps secure buy-in for AI and automation initiatives, making it easier to justify and obtain necessary funding for strategic investments.
Evaluating Long-Term Implications: AI and automation projects often come with ongoing requirements for maintenance, support, and scalability. A governance framework ensures these long-term factors are considered from the outset, allowing organisations to plan effectively. This comprehensive view helps mitigate risks, reduce unexpected costs, and ensure that adopted solutions remain viable and sustainable well into the future.
➡️ What strategies are important for AI and automation governance?
Governance is critical for scaling new technologies like AI and automation because it ensures that innovation aligns with business objectives, optimises resource use, and mitigates risks. An effective governance framework provides a structured approach to prioritising initiatives, managing demand, and ensuring long-term sustainability, enabling organisations to adopt and scale emerging technologies without disrupting daily operations.
Key Requirements for AI and Automation Governance:
1. A Clear and Well-defined Framework for Decision-Making: An AI and automation governance framework outlines a structured approach to evaluating, prioritising and implementing AI and automation initiatives. It removes the guesswork and helps organisations focus on the right AI and Automation candidates for their needs. If you’d like to know more about establishing an AI and Automation Framework you can watch this video:
VIDEO: How Technology Leaders Can Build AI and Automation Governance in 5 Steps:
2. Alignment with Business Objectives: Governance frameworks must ensure AI and automation initiatives are strategically aligned with clear business objectives to prevent resource wastage and avoid distractions from unplanned or low-priority opportunities.
3. Stakeholder Collaboration: Effective governance needs to promote strong alignment between business and IT, fostering trust and shared ownership of AI and automation projects.
4. Proactive Risk Mitigation: Governance practices must consider long-term risks by integrating maintenance, support, and scalability considerations early to avoid unexpected costs or disruptions.
5. Confidence Building in Technology Adoption: A robust governance structure needs to reduces risk aversion by clearly defining steps for implementation, minimising fears of failure, and increasing trust in AI and automation solutions.
6. Ethical AI and Compliance Assurance: Governance requirements should embed ethical considerations and regulatory compliance into the development and deployment of AI, ensuring responsible and sustainable adoption.
7. Empowerment of Decision-Makers: Governance frameworks must provide IT leaders and stakeholders with the tools, insights, and support needed to make informed decisions that enhance outcomes and improve service delivery.
➡️ How can Stakeholders Embrace and Support AI and Automation governance?
For IT Leaders: AI and automation governance demystifies these technologies, providing clarity on how to align investments with strategic business goals. Establishing a governance framework offers IT leaders a valuable opportunity to build stronger relationships with key business stakeholders. By demonstrating tangible wins and benefits, IT leaders can foster collaboration and take stakeholders on an exciting journey of innovation and transformation that they actively contribute to. Key areas of focus need to include:
- Ownership and Advocacy: IT leaders should take responsibility for defining, implementing, and overseeing AI and automation governance frameworks.
- Clear Communication: Proactively communicate the vision, benefits, and expected outcomes of governance to all stakeholders.
- Enablement: Equip their teams with tools, training, and best practices to align their efforts with governance requirements.
- Accountability: Monitor and report on governance compliance and ensure alignment with business objectives.
For Business Stakeholders: It demonstrates how AI and automation can deliver tangible business value, fostering collaboration and trust. Key areas of focus need to include:
- Active Collaboration: Participate in decision-making and provide insights into business needs to ensure governance aligns with organizational objectives.
- Ownership of Outcomes: Take shared responsibility for the success of AI initiatives and their alignment with ethical and business goals.
- Change Champions: Advocate for AI and automation within their areas, helping to dispel fears and promote understanding of the benefits.
For Teams (Business & IT):It provides clarity on roles, responsibilities, and the long-term impact of automation initiatives. Key areas of focus need to include:
- Adherence to Governance: Embrace governance guidelines in their day-to-day work, ensuring compliance with ethical, operational, and strategic standards.
- Skill Development: Stay up to date with AI and automation trends through training and certifications to effectively implement governance directives.
- Feedback Loop: Provide on-the-ground insights and feedback to refine and improve governance frameworks.
For Organisations: It reduces the risk of failed AI projects and ensures sustainable, impactful innovation. Key areas of focus need to include:
- Cultural Shift: Foster an organizational culture that embraces change, values innovation, and sees governance as an enabler, not a constraint.
- Investment in Resources: Allocate the necessary resources, including technology, people, and training, to support governance practices.
- Unified Vision: Align all levels of the organization to a shared vision for ethical and effective AI and automation use.
- Recognition of Success: Celebrate milestones and successes to reinforce the importance of governance and its positive impact on organisational growth.
As AI and automation continue to revolutionise industries, their adoption is no longer optional but a strategic imperative. However, the rapid pace of innovation brings both opportunities and challenges. Developing a robust AI and automation governance capability is critical for organisations to ensure that these technologies drive meaningful outcomes, align with business objectives, and foster ethical and sustainable practices.
Governance frameworks provide the foundation for informed decision-making, stakeholder alignment, and risk mitigation, empowering organisations to navigate this transformative era with confidence. By embracing governance, IT leaders, business stakeholders, teams, and organisations as a whole can collaborate effectively to unlock the full potential of AI and automation, ensuring long-term success and innovation.
With a clear structure in place, progressive organisations not only adopt AI and automation but master their implementation to achieve measurable impact and transformative growth.