{"id":26972,"date":"2025-01-07T11:18:21","date_gmt":"2025-01-07T11:18:21","guid":{"rendered":"https:\/\/www.dataiq.global\/?post_type=article&p=26972"},"modified":"2025-01-07T11:18:21","modified_gmt":"2025-01-07T11:18:21","slug":"frontline-lessons-ai-preparation","status":"publish","type":"article","link":"https:\/\/www.dataiq.global\/devstage\/articles\/frontline-lessons-ai-preparation\/","title":{"rendered":"Frontline lessons for organisational AI preparation"},"content":{"rendered":"

Laying the groundwork for AI adoption<\/span><\/b>\u00a0<\/span><\/h4>\n

The first step in preparing for AI involves aligning organisational processes with the demands of this selected AI technology. <\/span>Dennis <\/span>described to the audience the initial efforts his team undertook, including building and adopting specific onboarding processes. These initial steps were essential to ensure that data, tools, and stakeholders were adequately prepared to work in AI-driven environments and were a core foundation for the rest of the journey.\u00a0<\/span>\u00a0<\/span><\/p>\n

BigID emphasises that AI preparation is not just about technology; it is about establishing processes and frameworks that set the stage for long-term success.<\/span>\u00a0<\/span><\/p>\n

DataIQ members have spoken at length about the challenges explaining to non-data professionals about the importance of why these steps are so essential. For a successful integration of new AI tools that can extract everything possible, there must be buy-in from organisational decision makers to get the correct frameworks and operations in place before attempting a data-driven journey.\u00a0<\/span>\u00a0<\/span><\/p>\n

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Leverage data catalogues to reduce risk<\/span><\/b>\u00a0<\/span><\/h4>\n

Data catalogues play a major role in reducing risks associated with AI. <\/span>Dennis <\/span>demonstrated how effective cataloguing can streamline data management, ensure compliance, and mitigate operational risks, emphasising the need for structured, accessible, and well-maintained data syste<\/span>ms. A robust data catalogue not only simplifies data access but also serves as a critical tool for risk management.<\/span>\u00a0<\/span><\/p>\n

Risk is a natural part of business, particularly when it comes to investing in new technologies such as AI, but it can be mitigated. Data leaders need to ensure a level of data literacy where those using the tools understand how and why risks can happen, but also how they can be addressed and pre-emptively stopped.\u00a0<\/span>\u00a0<\/span><\/p>\n

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Security and architecture<\/span><\/b>\u00a0<\/span><\/h4>\n

Implementing AI-driven changes requires robust security measures. <\/span>Dennis <\/span>highlighted the challenges his organisation faced in ensuring data protection while adapting to new technologies. These measures were not only necessary for compliance but also had a significant impact on the organisation\u2019s overall architecture.<\/span>\u00a0<\/span><\/p>\n

Security must be a foundational element of any AI strategy, influencing how systems are designed and managed. Without security, business will open themselves up to a whole host of issues and regulatory problems. It does not matter where on the AI or maturity journey an organisation is, a solid approach to security will drastically heighten capabilities and culture.\u00a0<\/span>\u00a0<\/span><\/p>\n

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Proactive actions<\/span><\/b>\u00a0<\/span><\/h4>\n

To remain competitive in the fast-evolving AI landscape, data teams must ensure they are running a proactive approach to data problems, not a reactive one. Dennis highlighted that his team had developed proactive approached that included anticipating future needs, addressing potential challenges early, and continuously optimising processes and tools. By staying ahead through proactive actions, teams can adapt to changes and weather turbulent trading cycles more effectively to maintain a competitive edge.<\/span>\u00a0<\/span><\/p>\n

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Common AI concerns<\/span><\/b>\u00a0<\/span><\/h4>\n

The session concluded with a lively Q&A segment where <\/span>Dennis <\/span>addressed pressing questions from the audience.\u00a0<\/span>\u00a0<\/span><\/p>\n