Biography
Biography: Mark Strefford
Abstract
Introducing AI and ML technologies into the enterprise, as with any IT project, has a number of challenges. A number of these are often comparable to the delivery of a standard IT project, such as ensuring there is a clear business outcome, a defined scope for delivery, stakeholder engagement, a suitably qualified team and the ability to measure progress as the project continues. However, there are subtle differences that if not addressed or the business and technology stakeholders are not made aware, can increase the risk, cause issues during delivery and ultimately and potentially cause the project to fail. With a muchhyped technology that is immature in its wide-scale enterprise adoption such as AI, a high-profile failure can set an organization back in its appetite to adopt this technology again in the near to medium term. The aim is to highlight some of the issues that are likely to arise, from understanding the organizations strategy for AI, structuring a project delivery approach, engagement with users, ensuring that you have the right mix of resources to deliver, how to integrate with wider systems, security, privacy and data controller concerns and subsequently some proven approaches to take in addressing these.