Strategic AI Readiness: A Framework for Global Organizations
- Jason Doucet
- Sep 10
- 5 min read
AI Readiness: Why Planning Matters
Like other major projects and transformations within organizations, it is always recommendable to ensure that a plan is established to successfully accomplish these significant changes. We propose that organizations approach AI readiness similarly to digitalization or ERP implementations and highlight some of the key considerations under this approach which should be contemplated :
1. Scoping and Awareness Building
Scoping is critical. “Time is money” and many organizations dive headfirst into a major project without taking the necessary time to evaluate not only the needs that have to be addressed but how can solutions maximize on benefits and value. From personal experience, taking the time at the start to scope and evaluate options saves on the time and money required later when the wrong solution is put in place or must be drastically changed in order reach desired outcomes.
Organizations should begin by engaging knowledge experts to understand the potential functions of AI. This process is akin to ERP or software selection, where an RFP process helps define requirements. Workshops and training sessions should be conducted to raise awareness among leadership about the possibilities of AI. This not only informs decision-making but also fosters a culture of innovation.
As AI solutions continue to be developed and introduced, it’s a safe bet that these learning sessions will not cover an exhaustive list of AI possibilities. Encouraging brainstorming and a “think outside the box” mentality regarding possible AI solutions could be a useful exercise to elevate engagement in the AI evaluation process.
2. Benchmark
Recent studies show that countries like China and India are leading in AI adoption, with rates exceeding 50%. This is largely due to centralized government initiatives, significant investment in AI infrastructure, and a cultural openness to automation. Singapore also ranks high due to its Smart Nation strategy and robust digital governance. In contrast, countries like Canada, the US, and many in Europe lag behind due to fragmented digital ecosystems, regulatory caution, and slower organizational change (a)(b).
Learn from the leaders! Organizations should get an understanding of the approaches used by early adopters and more importantly the key success elements of these AI solutions put in place.
3. Strategic Alignment
AI initiatives must be aligned with the organization's strategic goals. Leadership should evaluate whether AI fills existing gaps, accelerates growth, or enhances competitive advantage. Will it allow for a reallocation of resources to higher value activities? Are these AI solutions the best alternatives for the organization? If AI does not directly support strategic objectives, a phased investment approach may be more appropriate. This step ensures that AI adoption is not just a trend-following exercise but a deliberate strategic move.
4. Leadership and Change Management
With the quick pace of AI introduction in organizations and societies, the negative impacts and hurdles impeding AI adoption or “AI Anxiety”(c) experienced by individuals in an organization should be considered when evaluating the approach taken by an organization in establishing its AI strategy. While the operational benefits of AI adoption may be compelling incentives for an organization, the human reactions to these changes and disruptions should be well understood and appreciated by the leadership as risk areas to be managed in order to ensure a successful transition. This was emphasized in a BCG 2024 (d) report which presented that 74% of organizations have yet to unlock the benefits and value from their AI initiatives, mainly stemming from the organization’s lack of emphasis and prioritization of the human aspects impacted by these investments and transitions.
Leaders must act as change agents, promoting the use of AI tools and encouraging experimentation. Emotional intelligence is critical in managing resistance and fostering a positive outlook toward AI. McKinsey's recent report (e) highlights that while employees are ready for AI, leadership often lags in implementation. Drawing parallels with ERP projects, successful change management involves clear communication, stakeholder engagement, and continuous support.
5. Tactical Team Formation
A dedicated tactical team should be formed to evaluate AI tools and solutions. From personal experience, the use of dedicated teams to a significant, companywide initiative has proven to be a factor which has contributed heavily to the success of the implementation. This team can be composed of part-time or full-time resources, depending on the organization's size and scope. Cross-functional and multicultural representation are also key factors in enhancing the project team's effectiveness, especially in global organizations (f).
6. Implementation Planning
Once the right AI tools are selected, a detailed implementation plan should be developed. This includes timelines, resource allocation, training programs, and risk mitigation strategies. The plan should mirror ERP implementation methodologies, ensuring structured rollout and minimal disruption. For projects that I have personally worked on, dedicated resources in the implementation process are a critical factor contributing to the overall adoption of the solution and success of the project.
7. Governance and Monitoring
Steering committees and leadership involvement are essential for monitoring progress. Regular reviews, feedback loops, and performance metrics help ensure that AI initiatives stay on track. Governance frameworks should also address data security, ethical use, and compliance with regulations established both within and outside of the organization.
8. Leverage AI
To guide the organization through its AI readiness and adoption exercise, why not use existing AI tools such as Copilot, ChatGPT or Claude.ai to help with the above-mentioned steps? These AI applications can provide guidance, suggestions and even produce working and presentation materials in PDF, Word or other formats to facilitate the process. In addition, AI can help with such things as identifying potential risk areas for your organization or even benchmarking with other organizations.
Conclusion
AI readiness is not a one-size-fits-all approach. Organizations must customize their strategies based on their unique needs and contexts. Drawing from ERP and digital transformation experiences, this framework provides a structured path to successful AI adoption.
Doucet Global Strategies offers tailored consulting to help organizations navigate this journey. Whether you're just beginning or refining your AI strategy, Doucet Global Strategies can help you turn readiness into results.
Sources:
a) AllAboutAI. (2025). The 2025 Global AI Adoption Report: Is Your Country on This List? Link
b) BytePlus. (2025). AI Adoption Rate by Country: A Global Technology Landscape Analysis. Link
c) International Journal for Innovative Research in Multidisciplinary Field (IJIRMF). (2024). AI Anxiety: A Theoretical Exploration of the Antecedents. Link
d) Boston Consulting Group. (2024). AI Adoption in 2024: 74% of Companies Struggle to Achieve and Scale Value. Link
e) McKinsey & Company. (2025). Superagency in the Workplace: Empowering People to Unlock AI’s Full Potential. Link
f) McKinsey & Company. (2024). Go Teams: When Teams Get Healthier, the Whole Organization Benefits. Link
About the Author
Jason Doucet - Principal Advisor & Founder, Doucet Global Strategies
Jason Doucet, CPA, is the founder of Doucet Global Strategies, a consultancy specializing in strategic advisory for globally operating organizations. With deep expertise in international business, cross-border taxation, and governance, Jason supports multinational enterprises, NGOs, and institutional investors with high-level, tailored solutions.
