The Rise of AI Platforms: Transforming Business Operations

Rosanne Kincaid-Smith, Group COO of Northern Data Group, notes the potential for AI to drive economic growth: “We’ve already seen how the power of AI can automate routine tasks, freeing up resources for other strategic initiatives in the business, and better personalise customer experiences. But now we’re also seeing businesses monetise their data by offering up their insights as a service to other companies, creating new revenue streams and opening up opportunities for innovation.”

The importance of data quality and integration

While AI platforms offer immense potential, their effectiveness heavily relies on the quality and integration of data. As Dr Kremer points out, “Data quality remains absolutely vital for the success of AI implementation. The principle ‘garbage in, garbage out’ still applies. An analogy would be constructing a building: if the foundation is weak, no matter how well-constructed the house above is, it will not be stable.”

However, van der Putten cautions against an overly rigid approach to data management: “Without data, no intelligence. However, the mantra ‘garbage in, garbage out’ is quoted too often and too easily. Getting all of your data in a single, structured place with no latency is a pipe dream. Lots of knowledge is hidden in unstructured documents, and real-time data is becoming more important, so you can’t afford to wait for it to turn up nicely cleaned in a central data store.”

Instead, he advocates for a top-down approach: “Don’t approach data bottom-up, but top-down. By building generative intelligence and automated decisions in interactions and workflows and letting AI learn from feedback, you will discover what data matters most and can become very targeted in your data quality and improvement efforts.”

Enabling new business models and innovation

AI platforms are not just improving existing processes; they’re enabling entirely new business models and revenue streams. Van der Putten envisions a future where “AI compliance and governance will become more important, but there will also be more emphasis on good and trustworthy use of AI, regardless of regulatory boundaries. Finally, we can expect that generative AI will be let out of its cage and gain more agency by giving it access to all kinds of tools and knowledge sources, becoming more autonomous in resolving issues or reaching certain goals.”

Dr Kremer foresees a range of innovative applications: “Automated negotiation bots can handle pricing and terms, transforming procurement and sales by securing better deals and optimising supply chains. Significant advancements in AI-driven personalised marketing will also arise, where LLMs create targeted campaigns, boosting customer engagement and sales. AI-powered virtual assistants will manage complex tasks and support strategic decisions, freeing up employee time.”

Challenges and considerations

While the potential of AI platforms is immense, implementing them comes with challenges. Organisations must carefully consider data privacy, ethical use of AI and the need for human oversight. Kincaid-Smith emphasises the importance of responsible AI development: “For proper data governance, companies with high-compute power must vet those accessing AI capabilities, assessing their credentials and intentions to mitigate negative impacts on employees and consumers. There will be a growing demand for professionals that understand how to build AI models ethically for management and data governance.”

The future of AI platforms

AI platforms represent a paradigm shift in how businesses operate and compete in the digital age. By providing powerful tools for data analysis, process automation, and decision-making, these platforms are enabling organisations to become more efficient, innovative, and customer-centric. As the technology continues to evolve, we can expect AI platforms to play an increasingly central role in shaping the future of business across all industries.

However, success with AI platforms requires more than just implementing the technology. It demands a strategic approach to data management, a commitment to ethical AI practices, and a willingness to reimagine business models and processes. Organisations that can navigate these challenges and harness the full potential of AI platforms will be well-positioned to thrive in the increasingly AI-driven business landscape of the future.

As AI technology continues to evolve, we can expect AI platforms to become even more sophisticated and integral to business operations. Dr. Kremer predicts: “AI platforms will support faster prototyping, allowing businesses to quickly validate use cases without extensive training periods. Often, AI products are combinations of multiple AI models, and these platforms enable quick assembly of such solutions.”

Van der Putten, meanwhile, anticipates a convergence of different AI technologies: “In future, we can expect that generative AI will be combined more with other forms of AI such as process mining and automated decisioning. An increased focus on actionability and scaling means AI and automation will converge more and more.”

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