How Decision Intelligence Supports AI-Ready Teams
AI agents and machine learning can help organizations make faster, more informed decisions. But even the best technologies can only go so far. To successfully implement these technologies, companies need AI-ready teams.
"AI-ready people is the idea of ensuring users and affected individuals have the necessary skills and willingness to fully leverage AI and use it to empower their abilities," says Gartner's 2024 Top Trends in Data & Analytics guide. In other words, professional development is a must to successfully implement AI.
Building AI-ready teams takes more than technical training. It also requires a shift in mindset. Gartner's research found that employees often describe AI as "complex" or "threatening." Many also feel overwhelmed by the pace of change. This psychological resistance slows adoption and limits the value companies get from AI-powered tools. In response, organizations are ramping up efforts to close the gap. By 2027, over half of CDAOs are expected to fund AI and data literacy programs to help teams better understand and use generative AI.
Decision intelligence platforms (DIPs) directly address this challenge, giving decision-making teams the tools and frameworks they need to accelerate adoption and make the most of AI agents. Before diving into how DIPs solve this problem, let’s take a look at what it means to have an AI-ready team.
Building AI-Ready Teams
To build AI-ready teams, organizations must focus on two equally important components: developing technical skills and fostering the right mindset. Let's explore each of these components in depth.
Technical Skills
Developing AI-ready teams begins with establishing foundational technical capabilities across the organization. According to Gartner, essential skills for AI-ready people include data/AI literacy, technical expertise, and AI stewardship.
Data and AI literacy is the cornerstone of AI readiness. It includes critical thinking and problem-solving skills that help employees understand business goals, policies, and how data flows into and out of AI platforms. This literacy shouldn’t be limited to data scientists. It needs to reach everyone, from executives to frontline staff.
Technical expertise refers to hands-on skills such as prompt engineering, assessing data quality, and validating AI findings. These abilities enable employees to work effectively with AI platforms and to recognize when AI-generated recommendations need further review or added context.
AI stewardship is often overlooked but essential. It involves curating and preparing data, reviewing AI outputs for accuracy, and training models to perform better over time. It also means understanding AI limitations, knowing the difference between probabilistic and deterministic models, and when to use each.
These technical skills should be tailored to different roles. For instance, executives need enough AI literacy to make informed strategic decisions, while those working directly with AI technologies require deeper technical knowledge in data handling and AI functionality.
Mindset Shift
Technical skills alone won't ensure that your team is AI-ready. The greater challenge in becoming AI-ready is psychological. For AI adoption to succeed, employees need to believe that these tools will enhance, not replace, their decision-making.
Organizations need to create psychological safety for experimentation with AI. This means demonstrating that mistakes are part of the learning process rather than performance failures. It also requires clearly redefining roles to emphasize how AI enhances human abilities.
This combination of psychological safety and clear role definition helps employees move from viewing AI as a threat to seeing it as a tool for personal empowerment and career advancement.
How Cloverpop Enables AI-Ready Teams
Cloverpop enables organizations to build AI-ready teams by addressing both sides of the readiness equation: simplifying technical skills needed and supporting the mindset shift required to adopt decision intelligence with confidence.
On the technical side, Cloverpop’s Decision Intelligence Platform embeds learning-by-doing into everyday work. D-Sight AI decision agents surface transparent, contextual decision recommendations across metrics, KPIs, and workflows — helping teams build data and AI literacy organically as they interact with real decisions. Cloverpop simplifies technical complexities like prompt engineering and data evaluation, allowing decision-making teams to focus on reviewing AI-generated insights in context, uniting human expertise with AI-powered agents without requiring deep data science knowledge.
Cloverpop also reinforces AI stewardship by showing how decisions are made, tracked, and improved over time. Built-in visibility into agent outputs, feedback loops, and outcome tracking helps teams understand when to trust AI, when to intervene, and how to improve AI performance — all critical skills for governing AI responsibly.
On the mindset side, Cloverpop helps organizations overcome resistance by making AI-powered agents accessible and collaborative. Rather than isolating AI in technical teams, Cloverpop integrates decision agents into shared decision workflows with clear team member role definitions. This helps teams see how AI enhances rather than replaces their expertise. Transparent interfaces, shared decision views, and intuitive tools foster a culture of experimentation, where learning and improvement are expected.
To accelerate both skill development and mindset change, Cloverpop’s Decision Success experts provide tailored onboarding and best-practice templates for executives, managers, and frontline teams. The result is faster adoption, deeper trust in AI-driven decisions, and stronger collaboration between people and technology.
By aligning technical skill-building with cultural transformation, Cloverpop helps organizations turn AI-ready teams into a competitive advantage — capable of faster, smarter decisions at scale.
Decision Intelligence Is the Key to AI-Ready Teams
Building AI-ready teams is a critical business priority. Organizations that successfully build AI-ready teams will have a competitive advantage. Meanwhile, organizations that fail to prepare their workforces risk implementing powerful systems that go unused or deliver suboptimal results due to human resistance or misunderstanding.
Decision intelligence platforms like Cloverpop help close this gap by embedding hands-on skill development directly into decision workflows with guard rails that align AI agents to support real-world team needs. With transparent, contextual recommendations and collaborative tools, decision intelligence platforms make AI feel approachable, trustworthy, and practical, accelerating adoption across technical and non-technical roles alike.
By addressing both technical skills and team mindsets, leaders can access the transformative potential when humans and AI collaborate for faster, better decisions. The best AI is only as effective as the people who use it, and decision intelligence gives them the mindset and tools to access its full potential.
Want to learn more about decision intelligence and other key trends shaping the future of data and analytics? Download the Gartner Top Trends in Data and Analytics Guide.