BCN Podcast: Not all AI is Equal

The amount of artificial intelligence tools available on the market is vast and multifaceted, often leading to confusion surrounding its implementation in business. In our latest podcast episode, Fraser Dear, BCN’s Head of AI and Data Innovation, and AI expert Andy James, discuss what AI truly encompasses alongside host Peter Filitz. The episode includes breaking down AI’s core categories: generative AI, data science, and process automation. To understand AI’s significance, we need to grasp its foundational definition. At BCN, we articulate AI as the capability of machines to emulate human intelligence. This involves sophisticated algorithms that perform tasks such as visual and speech recognition, decision-making, and language translation. These attributes contribute to the seamless integration of AI across platforms; significantly Microsoft technologies, such as Azure and the Power Platform, where they facilitate efficient workflows and data communication.

Creating and replicating content with generative AI

The first category, generative AI, is where the excitement often kicks off. It can involve replicating existing content or creating something new; be it text, images, or music. This segment highlighted various models, such as GPT, Copilot and other emerging technologies, which serve distinct purposes based on their underlying architecture and design. For instance, GPT excels at generating coherent text while Llama is oriented toward high-performance research. Understanding these differences is crucial for businesses looking to leverage generative AI for targeted outcomes.

Data science workloads: the backbone of AI applications

Next, we shifted our focus to data science workloads, which are the backbone of AI applications in today’s world. Machine learning, natural language processing, and computer vision exemplify how businesses can use data-driven insights to foster customer engagement, automate tasks, and ultimately enhance operational efficiency. For example, recommendation systems on streaming platforms employ algorithms that analyse past user behaviour to suggest what they might enjoy next. This same logic applies in various commercial contexts, allowing businesses to predict customer preferences and personalise their offerings.

Streamlining business operations

The discussion then progressed to process automation, illustrating how AI can streamline workflows by automating repetitive tasks and improving accuracy. We shared practical examples, including using AI for document processing, which reduces human error and operational costs. As businesses increasingly find themselves grappling with large volumes of unstructured data, AI becomes an indispensable tool for extracting valuable insights.

Choosing the right AI model for your business needs

Fraser and Andy also emphasised the importance of choosing the right AI model for specific business objectives. The analogy of transportation elucidated this notion perfectly: like selecting a bike for a paper route versus a plane for long-distance travel, businesses must discern what type of AI best serves their needs. With that premise, the conversation expanded to how Microsoft’s Azure serves as a comprehensive backbone to many AI applications, offering customisable solutions tailored to unique company challenges.

Helping businesses begin their AI journey

To support organisations embarking on their AI journey, several “AI Kickstarters” were introduced. These tailored initiatives aim to assist businesses in identifying their specific pain points and matching them with appropriate AI solutions for immediate benefits. The varying offerings include chatbot deployments and automating data extraction processes which exemplify how businesses can incrementally integrate AI into their operations without overwhelming existing systems.

The episode provides listeners with actionable insights into the diverse and evolving world of artificial intelligence. By understanding that not all AI is equal and having a better understanding of what AI is best used where, organisations can effectively and safely use this technology, paving the way for a future defined by innovation and efficiency.