top of page
Search

Stages of AI Confidence: How to Measure and Improve AI Skills


Artificial intelligence has and is transforming the way we work, making processes more efficient and decision-making more data-driven. Yet, for many business leaders and teams, adopting AI can feel overwhelming. Understanding the different stages of AI confidence can help you assess where you are and what steps you need to take to build your team's skills. Whether you are just beginning your AI journey or looking to optimise existing tools, improving AI confidence is key to making the most of these technologies.


In this blog, we explore the stages of AI confidence and practical ways to develop your skills in a way that is simple, engaging and effective.

Stage 1: Awareness – Recognising the Role of AI

At this stage, as an individual or organisation, we are aware that AI exists and understand that it plays a role in business. However, there may be uncertainty about how it works or how it applies to our organisation.


Example

A business leader hears about AI-driven customer support chatbots but is unsure how they could benefit their team. They know AI is important but have not yet explored how it fits into their strategy.


How to Improve

  • Read introductory articles and case studies about AI applications in your industry.

  • Attend AI-focused webinars or conferences to gain foundational knowledge.

  • Have open conversations with peers or industry experts to learn from their experiences.


Stage 2: Familiarity – Exploring AI in Practice

At this point, you have started learning about AI and may have experimented with simple AI tools. You and your team understand basic concepts but may still lack the confidence to implement AI-driven solutions at a larger scale.


Example

A customer service team in a logistics company begins using AI-powered chatbots to handle routine customer inquiries, such as delivery status updates or tracking requests. However, the team still relies on manual intervention for complex issue resolution and customer escalations. While they acknowledge the efficiency gains from AI automation, they hesitate to delegate more critical CX processes to AI due to concerns about accuracy, customer sentiment analysis, and escalation handling.


How to Improve

  • Experiment with free or low-risk AI tools such as chatbots, automated scheduling or predictive analytics.

  • Engage in hands-on training to build confidence in using AI-driven solutions.

  • Encourage team discussions about AI applications to normalise its use in everyday workflows.


Stage 3: Adoption – Integrating AI into Workflows

At this stage, your organisation actively uses AI in daily operations and trusts its capabilities. AI is no longer just a concept but a tool that helps us work more efficiently.


Example

An HR team uses AI-driven software to screen job applications, reducing the time spent on initial reviews and allowing them to focus on personalised interviews.


How to Improve

  • Identify repetitive tasks that can be automated to free up time for more strategic work.

  • Invest in AI training to ensure teams feel equipped to use AI-driven tools effectively.

  • Seek feedback from teams to refine AI implementation and address any concerns.

Stage 4: Confidence – Leveraging AI for Decision-Making

At this point, AI insights are trusted and used to support decision-making. AI is integrated into strategies and seen as a valuable asset.


Example

A customer experience (CX) team in a utilities company relies on AI-driven sentiment analysis to detect customer dissatisfaction in real-time and proactively adjust service offerings. AI insights guide decision-making in personalising responses, improving service quality, and reducing customer churn.


How to Improve

  • Develop a data-driven culture where AI insights are regularly reviewed and used for strategic planning.

  • Provide leadership training on AI decision-making to ensure informed and ethical AI use.

  • Stay updated on AI trends to continuously optimise AI-driven processes.


Stage 5: Mastery – Innovating with AI

At this level, organisations not only trust and use AI but also look for ways to innovate and push boundaries. AI is a key driver of business transformation.


Example

A company develops its own AI-powered customer experience tool, tailored to its specific needs. AI is embedded in company culture, and teams are confident in leveraging its full potential.


How to Improve

  • Explore AI-driven innovation by testing new technologies or custom AI solutions.

  • Encourage AI literacy across all departments to ensure AI expertise is widely distributed.

  • Collaborate with AI experts and partners to refine strategies and stay ahead of industry trends.


Moving Forward with AI Confidence

AI confidence is not built overnight. It is a journey of learning, experimentation and growth. By understanding where your organisation stands in these stages, you can take meaningful steps to improve your AI skills and integrate AI in ways that support your goals.


📩 Are you ready to build AI confidence in your organisation? At Envisago, we can help you assess your AI maturity and develop strategies for AI adoption. Contact us today to start your journey toward AI-driven transformation.


 
 
 

Comments

bottom of page