In an engaging discussion with Emma, a Senior Consultant at KPMG UK, I gained a deeper understanding of the multifaceted world of artificial intelligence and the critical role her team plays in assisting clients with constructing robust AI infrastructures. Emma’s professional yet approachable demeanor made our conversation both insightful and captivating.
“AI isn’t just a buzzword anymore,” Emma began, her enthusiasm palpable. “It’s a transformative force reshaping industries globally. However, building an AI infrastructure is far from a one-size-fits-all process. Each organization presents unique needs, challenges, and goals.”
Emma’s responsibilities at KPMG involve closely collaborating with clients to grasp these unique variables. “It’s essential to start with a clear understanding of what the client aims to achieve with AI,” she explained. “Are they striving to enhance customer experience, improve operational efficiency, or gain deeper insights from their data? Once we have a clear objective, we can begin to design an infrastructure tailored to those needs.”
One of the initial steps involves assessing the current state of the client’s data. “Data is the cornerstone of any AI initiative,” Emma noted. “We conduct comprehensive data audits to evaluate the quality, completeness, and relevance of the existing data, identifying any gaps or issues that need addressing before moving forward.”
In this context, Emma emphasized the importance of data governance. “Data governance frameworks are critical for ensuring data integrity and compliance,” she said. “We work with clients to establish robust governance policies and practices, including data privacy, security, and ethical considerations. This not only helps build a trustworthy AI system but also ensures that AI models are fair and unbiased.”
With the data foundation in place, the next step involves selecting the right technologies and tools. “There are numerous AI technologies available today, from machine learning algorithms to natural language processing tools,” Emma explained. “Our role is to help clients navigate this landscape and choose the technologies that best align with their goals and capabilities. Scalability is also a key consideration, as the AI infrastructure needs to grow with the organization.”
Emma illustrated these concepts with a compelling case study from a recent project. “We worked with a retail client who wanted to enhance their supply chain management using AI,” she recounted. “After conducting a thorough data audit and establishing a governance framework, we recommended a combination of machine learning algorithms and predictive analytics tools. These technologies enabled the client to forecast demand more accurately, optimize inventory levels, and reduce costs.”
Collaboration and skills development are also critical aspects of building AI infrastructure. “AI projects require a diverse set of skills, from data science to software engineering,” Emma pointed out. “We often work alongside the client’s internal teams, providing training and support to ensure they have the necessary expertise to maintain and evolve the AI infrastructure. This collaborative approach helps build internal capabilities and fosters a culture of continuous learning and innovation.”
Emma also addressed the ethical considerations in AI. “Ethics in AI is a growing concern, and rightly so,” she said. “We guide our clients in implementing ethical AI practices, which encompass transparency, accountability, and fairness. This involves not only the technical aspects but also organizational policies and culture.”
As our conversation drew to a close, I asked Emma about the future of AI infrastructure. “The future is incredibly exciting,” she replied with a smile. “Rapid advancements in AI technologies present endless possibilities. However, it’s crucial to approach AI with a strategic mindset, focusing on long-term value rather than short-term gains. At KPMG, we are committed to helping our clients navigate this journey, building AI infrastructures that are not only advanced but also responsible and sustainable.”
Walking away from the interview, I felt inspired by Emma’s insights. Her passion for AI and dedication to helping clients harness its potential was evident throughout our conversation. Building an AI infrastructure is undeniably a complex, multifaceted process, but with the right guidance and expertise, organizations can unlock tremendous value and drive meaningful transformation.