CIOReview | | 19 NOVEMBER 2023Advising clients in the AI field poses a challenge due to the absence of matured and well-proven frameworks and standards to address AI-related risks. This problem arises from fundamental disparities between AI solution development, including generative AI, and traditional software development relying on standard application services. Existing quality measures within organizations are not easily applicable to AI solutions.Lauberg Consulting offers assistance in recognizing and addressing significant AI-associated risks and provides guidance to overcome challenges during AI implementation. These steps are crucial for developing resilient and dependable AI solutions over an extended period. The primary goal of establishing an AI risk framework is to safeguard human and, in particular, vulnerable children's well-being and mitigate potential financial and reputational damages.Expanding current testing capabilities is essential to ensure reliable solutions, maintain data quality, and prevent biased outcomes. It's vital to establish governance safeguards within the framework throughout the AI technology development lifecycle and afterward during the maintenance and support of AI products and services. Lauberg Consulting can assist in assessing clients' current positions and guiding their path toward maturity, emphasizing experimenting with smaller projects, exploring new uses, and launching pilot initiatives.The company focuses on evaluating potential risks, specifically in terms of cybersecurity. Despite the numerous advantages offered by AI and generative AI, maintaining a balance between these benefits and risks is crucial, especially when safeguarding against cyber threats. The risk landscape in this field constantly shifts due to malicious actors using AI techniques, which can enhance the effectiveness of ransomware attacks. Continuous efforts are made to develop efficient countermeasures to tackle this issue.Lauberg Consulting collaborates with second-line functions to implement effective risk management measures and policies. It assists them in writing policies by analyzing the stakeholder landscape and identifying pain points within clients' organizations. It also assesses the maturity of their current systems and advises on the careful integration of AI measures, highlighting the need for additional precautions. An example could be to ensure proper opt-out options for solutions with AI embedded. Although not a precise method, the focus is on determining what would bring the greatest benefit rather than following a strict formula. The goal is to enable organizations to seize AI opportunities while minimizing potential risks. The ultimate objective is to apply AI by choice to optimize business value rather than because it is the only cost-effective technical solution from tech vendors."I have over 20 years of expertise in various industries, including finance, pharma, and the public sector, delivering IT implementation programs, IT operations and service management framework improvements, and training. I am now venturing into the critical infrastructure sector, which shares comparable regulatory demands. Currently, I am actively involved with a client delivering wind farm projects within the United States," says Lauritsen.The impact of generative AI will be significant and potentially disruptive. Though it may offer short-term benefits, it could also incur long-term costs. By collaborating with Lauberg Consulting, organizations can establish ethical values and principles to help prioritize AI applications within clear boundaries and ensure sustained success with AI in the long run. We have the competencies and experience to support organisations in the development of AI strategy and governance and safely navigate the minefield of generative AI
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