Organisational AI Checklist 

Discover the Organisational AI Checklist to prepare your workforce for successful AI adoption. Learn how to build technical readiness, close skill gaps, foster employee trust, and align leadership with strategy to unlock AI’s full potential.
 

The rapid integration of AI into the workplace is reshaping business models, customer engagement, and employee roles. While the opportunities are immense, so are the challenges, particularly around workforce readiness, skill gaps, and organisational adoption.

A recent survey of over 1,000 technology and business leaders revealed that 42% of companies abandoned most of their AI pilot projects by the end of 2024, a sharp rise from 17% the previous year. The reasons extended beyond technical complexity. In many cases, projects failed due to human factors such as employee resistance, skepticism, and insufficient skills.

Why human capital matters

Employees’ perception of AI is critical to successful adoption. If workers view AI as a threat, resistance is inevitable. If they see it as an opportunity, they become champions of transformation. Companies must treat their workforce as a core strategic asset, investing in continuous training, upskilling, and reskilling to unlock long-term value.

Successful AI adoption requires more than new tools, it requires individuals who embrace change, innovate with new models, and create customer value. Organisations that view employees not merely as resources but as human capital will be better positioned to realise AI’s potential.
 

Building an AI-ready organisation

AI adoption is most effective when technology, people, and organisational structures evolve together. CMOs, with their dual focus on customers and cross-functional influence, play a pivotal role in leading this alignment.

1. Technical readiness
• Audit AI tools and use cases: Map which AI systems will be implemented and align them to specific roles and processes.
• Demonstrate impact through pilots: Launch small-scale pilots to showcase tangible benefits (e.g., how AI can support campaign optimisation, customer segmentation, or content personalisation), building credibility with both stakeholders and employees.

2. Organisational readiness
• Conduct a skills assessment and gap analysis: Evaluate current capabilities to identify where reskilling and new expertise are needed.
• Bridge gaps through training: Provide tailored programs in AI literacy, data interpretation, digital fluency, and emerging technical skills. Formats may include workshops, certifications, online modules, or hands-on projects.

3. Human factors
• Build trust and transparency: Employees need to understand how AI supports their roles and contributes to business success. Clear communication reduces fear of job displacement.
• Promote security and opportunity: Highlight paths for employees to become domain experts and leaders in AI-enabled functions.
• Foster confidence in AI outputs: Consistent, reliable, and explainable AI systems strengthen trust in AI-driven decisions.

4. Leadership & change management
• Embed AI in business strategy: Position AI not as a standalone initiative but as a core enabler of customer experience, personalisation, and efficiency. 

 

Checklist 

1. Technical readiness

☐ Audit AI tools and platforms to be used across the organisation
☐ Map which roles and processes each AI tool will support
☐ Launch small-scale pilot projects to demonstrate AI’s real-world impact
☐ Share pilot results with employees and stakeholders to build credibility
 

2. Organisational readiness

☐ Conduct a skills assessment to evaluate current workforce capabilities. The ADMA Capability Compass ™ is your data-driven solution to uncover, understand, and elevate your marketing team’s skills – so you’re not just keeping up with change, but leading it.
☐ Perform a gap analysis to identify missing skills critical for AI adoption
☐ Develop targeted training programs (AI literacy, digital fluency, technical skills)
☐ Provide diverse training formats: workshops, online courses, certifications, hands-on practice. Be sure to check our the ADMA course guide for courses designed by industry, for industry.
☐ Integrate AI initiatives into the overall business and marketing strategy
 

3. Human factors

☐ Communicate how AI supports employees
☐ Build trust and transparency by explaining AI decision-making processes
☐ Reinforce job security while highlighting opportunities for upskilling
☐ Foster employees to become domain experts in AI-enabled functions
☐ Promote confidence in AI outputs by ensuring systems are reliable and consistent
 

4. Leadership & change management

☐ Treat employees as strategic assets (human capital), not just resources
☐ Encourage a culture of adaptability and innovation
☐ Align technology, people, and organisational structures to work in tandem
☐ Position AI as a driver of customer experience, personalisation, and growth
 

Want to know more?
To understand the opportunities and challenges AI presents for marketing and to learn how to balance innovation with trust, creativity and responsibility, download ADMA’s AI, Talent & Trust: A new blueprint for marketing leadership.