AI or Applied AI? What’s the difference and why is it important?

Matt Dickson & David Yip | February 13, 2024

In the rapidly evolving landscape of technology, Artificial Intelligence (AI) stands as a beacon of innovation, driving change across industries. However, as business leaders navigate this new frontier, a critical distinction emerges between AI and Applied AI. Understanding this distinction is not just academic; it's foundational for any senior executive or business looking to harness AI's potential effectively.


The Essence of AI vs. Applied AI

AI is a fascinating technology, with seemingly magical capabilities—the algorithms, computational models, and systems capable of performing tasks that traditionally require human intelligence. This includes everything from understanding natural language to recognising useful patterns in data autonomously. Applied AI, on the other hand, is about leveraging this technology in real-world applications to solve specific business problems. It's the difference between developing a sophisticated machine learning model and using that model to improve customer service or streamline operations.


Why the Distinction Matters

The distinction between AI and Applied AI matters because it highlights a fundamental truth: technology alone is not a silver bullet. Success in the digital age requires not just technological or process innovation but their thoughtful application – in particular, how your people will become more productive, creative and resilient through the use of technology, with your customers and company to benefit.

1. Strategic Alignment: Applied AI underscores the importance of not just aligning AI initiatives with strategic business objectives, but with workforce capabilities and organisational culture. It's about re-evaluating your business strategy and value proposition and re-aligning your enterprise resources and human capital for new opportunities and threats.

2. Human Capital: Emphasising Applied AI brings human capital into focus. As AI technologies develop, the role of people in the organisation evolves. Businesses need to uplift and build new capabilities in their teams, ensuring they can confidently harness the power of AI as their “co-pilots” to deliver new value to the organisation.

3. Cultural Shift and Experimentation: Adopting Applied AI necessitates a cultural shift towards experimentation and learning. Companies must foster an environment where staff at all levels – from frontline employees to board directors – are encouraged to engage with AI, understand its benefits, and contribute to its implementation.


The Importance of Getting Hands-On

The need for hands-on experience with AI across the organisation cannot be overemphasised. This approach demystifies AI, making it more accessible and understandable to everyone. It also enables businesses to identify practical applications of AI that can drive immediate value from across the organisation.


Risks and Rewards

While the potential benefits of AI and Applied AI are vast, there are also risks to consider, including the implications of automation on the workforce, data privacy concerns, and the ethical use of AI technologies. Conversely, the risk of inaction—of failing to engage with AI—can leave businesses lagging in an increasingly competitive and technology-driven marketplace.


Calls to Action

For businesses looking to navigate the complexities of AI and Applied AI, the path forward involves strategic planning, investment in human capital, and a commitment to continuous learning and adaptation. Here are three calls to action:

1. Strategic AI Roadmapping: Develop a comprehensive AI strategy that aligns with your both your business objectives and workforce capabilities. Identify areas where AI experimentation and learning can be done and outline a roadmap to further use case discovery and implementation strategies for scaling.

2. Capability Building and Culture Change: Assess your organisation's readiness for AI, identify skill gaps, and design programs to uplift your team's capabilities in AI, data and digital, as well as new ways of working. This includes fostering a culture of innovation and experimentation.

3. Ethical AI and Risk Management: Ensure your AI initiatives are ethically responsible, compliant with regulations, and equipped with robust risk management strategies to mitigate potential negative impacts.

In conclusion, the distinction between AI and Applied AI is not just semantic; it represents an appreciation of the critical human capital and workforce transformation considerations that are critical to harnessing AI's full potential. By focusing on Applied AI and ensuring people are well-equipped with the skills and behaviours to flourish, companies can ensure that their investments in technology translate into real-world value, driving innovation, efficiency, and competitive advantage in the digital era. The journey toward AI excellence is complex and requires strategic vision, a commitment to human capital, and an unwavering focus on practical application. With the right approach and expert guidance, businesses can navigate this journey successfully, unlocking new opportunities for growth and transformation.