According to Gartner, a staggering 85% of AI projects fail to deliver on their expected outcomes, often due to poor planning, data quality issues, and misaligned objectives.
Why it matters: Better-organized AI and data projects are essential for maximizing the value these technologies bring to your business. To achieve business objectives through data and AI, organizations must establish a clear framework for project management, data governance, and cross-functional collaboration.
The solution: By implementing a human-centric approach, organizations will ensure that technology solutions are not just using the data but leveraging it in a way that is practical and ethical while meeting the needs of stakeholders and users. Ultimately, a human-centric approach to data and AI projects can lead to more impactful solutions that deliver real value to their users.
What you’ll learn in the white paper:
- How to align AI projects with business objectives.
- The main pitfalls in each phase of data and AI product development.
- How to implement a problem-driven, human-centric approach throughout the project lifecycle and ensure seamless collaboration between all stakeholders.
- Best practices for ensuring measurable impact.