In the new AI World - Business requires an AI Operating Model

A survey by Vention found that over 80% of businesses have embraced AI to some extent, seeing it as a core technology within their organisations. Furthermore, 35% of these companies are using AI across multiple departments. 80% of executives are convinced that automation can be applied to any business decision. The message is loud and clear: Don’t let your organisation fall behind in harnessing AI’s transformative power.

Leaders must actively explore and define how AI can redefine their industries, from automating processes to creating new product categories and business models. The future of innovation lies in our ability to envision a world where AI’s potential is fully integrated into the fabric of organizational creativity and growth.

The key to success lies not in the technology itself but in designing a new operating model to unleash its true value. Companies need to undergo a systemic transformation by integrating AI and autonomous processes across all functions to achieve higher levels of efficiency, creativity, and growth. This necessitates designing a new native AI operating model across People & Capabilities, Technology, Culture and Organisation. Without this, AI investments may fail, as Bloomberg experienced in March 2023 when they invested over $10 million to create a custom LLM for financial analysis, only to find that the next version of GPT released months later outperformed their custom model. This case highlights the challenge faced by companies seeking to surpass the capabilities of widely available, cutting-edge AI technologies like GPT, which are accessible globally for a minimal fee.

The true potential lies in transforming towards sovereign innovation, leveraging multi-agent systems, and developing a new AI-native operating model that could significantly alter industry dynamics. It’s essential to frame internal discussions not just at the individual level—like improving efficiency—but to consider whether existing functions or processes are necessary and how these fit into the broader company context. An AI-driven operating model can provide a significant competitive edge. This advantage stems from the accessibility of powerful technologies and APIs, such as OpenAI. However, simply having access to these technologies is not enough. To truly harness AI’s potential, companies must integrate it with their proprietary data and broader operating systems. Without this comprehensive approach, achieving a competitive advantage will be challenging. The AI economy requires a new business architecture and operating model emphasising agility, innovation, and ethical considerations. Adapting to these changes is crucial for businesses to remain competitive.

Proposed AI Operating Model

Let us break-down each element of the proposed new AI Operating Model.

AI Strategy

The plan of action to achieve the desired level of AI maturity within the organization. This may involve using AI for automation, predictive analytics, natural language processing, or other applications to improve an organisation's efficiency, decision-making, and innovation. A robust AI strategy often includes considerations such as data acquisition, model training, ethical guidelines, and integration with existing systems.

Leadership

Organisations must change how they think, act, and learn to use AI. It is crucial to actively promote experimentation, investment, learning, and responsible stewardship. Regarding leadership, fostering a culture of experimentation, investment, and ongoing education is essential. Communicate your vision of the AI world to your team, explaining its benefits and roles. Aim for a comprehensive approach to AI integration, which might involve collaborating with external IT environments or agencies to circumvent rigid internal policies.

Talent & Culture

Upskilling current employees, attracting and integrating new skills, and fostering AI-first mindsets and behaviours are crucial for talent and culture. When it comes to demonstrating the value of AI, it's essential to showcase tangible benefits early on, especially to sceptics. Roles, skills and performance measures required for people to successfully build and/or work with AI. Start by introducing AI through small, manageable projects, even on a personal level, to maximise exposure.

Processes & Business Model

New business processes, methods for working with suppliers and ecosystem partners, and ways to generate revenue from data and intellectual property will need to be designed.. When it comes to processes and business models, partnerships are essential. Identify areas where your company can reap the greatest benefits and concentrate your efforts there. It's important to see risk and compliance teams not as hindrances but as vital partners in managing risk.

Ideally, your business architects will be able to describe value streams for each identified process to ensure a genuinely customer-centric approach is integrated into the AI business architecture. Value streams are easy and quick to use and clearly show how value is delivered to the customer. The business processes that require redesign due to the impact of artificial intelligence and the necessary redevelopment of business capability supporting applications to incorporate artificial intelligence.

 Data & Technology

The data is required to support specific AI techniques defined by the AI Strategy. This will intelligently encompass external and internal data, supported by proprietary 'co-pilot' tools that aid in new processes. Concentrate on identifying data sets that can offer a competitive advantage. Having an API-driven IT architecture is crucial when dealing with data and technology. With this foundation, integrating advanced systems will prove to be relatively easy. Consider the overall technical infrastructure and tools needed to train, deliver and manage AI Models across their lifecycle.

Governance & Ethics

Governance encompasses the policies, processes, and relevant technology components required to ensure safe, reliable, accountable, and trustworthy AI solutions. Well defined by Practice Director Data & AI AltrumAI Gurpreet Sing D.:

“AI Governance encompasses the policies, frameworks, and practices that operationalise these ethical considerations, ensuring they're not just theoretical ideals but integral parts of AI's lifecycle. AI Ethics informs the principles behind AI Governance, and AI Governance provides the structure needed to implement ethical AI. ”

Net positive impact

New approaches to managing risk, security, privacy, sustainability, and safety are crucial to ensure a net positive impact. Regarding data and technology, ensuring that your IT architecture is API-driven is essential. Without this foundation, integrating advanced systems will be challenging. Focus on identifying data sets that can provide a competitive edge.

In conclusion, an AI Operating Model is essential for companies aiming to reach a mature stage in their AI journey. It provides a structured framework that aligns business objectives with AI capabilities, ensuring that organisations can effectively integrate artificial intelligence into their operations. By establishing transparent processes, roles, and governance, businesses can mitigate risks and harness the full potential of AI technologies. This model facilitates better decision-making and resource allocation and fosters a culture of innovation and adaptability within the organisation. Ultimately, embracing an AI Operating Model positions companies to navigate the complexities of the AI landscape and drive sustainable growth in an increasingly competitive market.