Generating value from AI

How do we enable organisations to generate value from AI?

In today's digital age, Artificial Intelligence (AI) and its subset Generative AI (GenAI), is a beacon of transformative potential; the game-changer organisations are seeking. It promises to revolutionise industries, reshape customer experiences, and redefine business operations.? However, while its potential is immense, the pathway to harnessing its true value remains complex for many organisations.? The goal of AI democratisation is proving illusive.? How does an organisation create an enabling capability to put AI in the hands of those that need it?

Understanding AI and GenAI

At its core, AI allows machines to emulate human-like cognitive functions, from learning and reasoning to problem-solving. GenAI, on the other hand, offers the unique ability to create new, previously unseen content or data based on patterns it has learned. Imagine AI as understanding a language, while GenAI crafts poetry in that language or AI understands the themes of a book, whereas GenAI can write the next chapter.

…and why so popular

GenAI has surged in popularity due to a combination of technological advancements, practical applications, and its inherent ability to delight:

1. Ability to Generate New Content: Unlike traditional AI models which analyze and process existing data, GenAI can produce entirely new content, whether it's images, text, music, or even design blueprints. This capability opens doors to numerous creative applications. For example, Unilever’s Homer, leveraging OpenAI ChatGPT API, generates an Amazon short and long product description taking only few details that matches the brand tone, helping marketing teams to generate quickly and efficiently product listings for their campaigns.
2. Innovation in Creative Fields: GenAI can assist designers, artists, and musicians by offering innovative designs, artwork, or compositions, acting as a collaborative tool that augments human creativity.
3. Cost Efficiency: Businesses can leverage GenAI to automate certain tasks that would traditionally require human intervention, such as content generation, design prototyping, and even customer interactions, leading to cost savings….think Co-pilot
4. Personalization: GenAI can be used to craft personalized experiences for users. For instance, creating bespoke marketing content tailored to individual user preferences.
5. Data Augmentation: In fields where data is scarce, GenAI can generate synthetic data, aiding in tasks like training machine learning models where large amounts of data are typically required.
6. Rapid Prototyping: In product design and development, GenAI can quickly generate multiple design variations, allowing for faster iterations and optimisation.? For example, Toyota Research Institute develops AI techniques to aid car designers, optimise product features, and create unique design options
7. Research and Drug Discovery: In the medical and pharmaceutical fields, GenAI can help in predicting molecular structures or simulating biological processes, accelerating drug discovery and research.
8. Public Engagement: Publicly accessible GenAI tools, like ChatGPT and Claude, have allowed a broader audience to experiment with and understand the potential of GenAI, leading to viral trends and greater awareness.
9. Ethical and Philosophical Discussions: GenAI also brings to the forefront intriguing discussions about creativity, authenticity, and ethics. As it blurs the lines between machine-generated and human-created content, it pushes society to reflect on the nature of creativity and originality.

The current AI conundrum

Despite its promise, many organisations find it challenging to extract tangible benefits from AI – the entire World seems in a rush to “get some AI”, without really asking why or indeed understanding how.? Do we build or buy?? What skills will we need and how will we source them? ?How will my business models and operating models change?? How do I get the right tools in the hands of the people that need them?? Where do I start?

Challenges are broad and deep and surface in all sectors, for example:

• Many TMT organisations face challenges such as protecting intellectual property rights, ensuring quality and originality, managing ethical and social implications, and building trust and credibility with audiences.
• Another example is in Government – using GenAI as a way to communicate with Citizens, when the content generated may suffer from errors, bias, misinformation or indeed hallucinations – rationale alone to ensure ‘human in the loop’

Centre of Enablement (CoE): A Catalyst for AI Democratization

Democratizing AI isn't just about tools; it's about fostering an ecosystem where AI's power is accessible across the board. This is where the CoE comes into play (and the E is enablement).? Creating a central capability that has a focus on enabling the entire value chain of the organisation, irrespective of maturity levels is critical to unlocking the value.

So what are the key tenets of a robust CoE?? Well I think they must include:

• Vision, Mandate & Strategy: Rooted in an Insight-Led Transformation (ILT) approach, ensuring AI initiatives resonate with business objectives and have clear organisational value, but coupled with a strategy that allows for flex and pivot (we’ve all seen just how fast this space is moving)
• Stakeholder Engagement & Comms: Consistent communication ensures alignment and buy-in from all parties involved.
• Operating Model: This covers skill enhancement, training, demand recognition, and innovation management, ensuring optimal AI tool utilization.
• Data: The lifeblood of AI. From acquisition and governance to modelling and exploitation, data management is paramount.
• Technology: Selection of the right platforms, tools, and deciding between bespoke or ready-made AI solutions like Co-pilot
• Risk & Compliance: Addressing the ethical, legal, and regulatory facets of AI.
• Customer Experience: Keeping in mind that every stakeholder is a 'customer', ensuring a comprehensive approach to continually delight your audience
• Business Case: Continuously evaluating the RoI of AI endeavours.
• Delivery Management: This entails the nitty-gritty, from procurement and project management to finance and resourcing.

Central to CoE's ethos is a persistent query: "Is this AI application adding value? Is it echoing with our organisational objectives?"

So, for businesses to truly harness the transformative power of AI, a strategic and structured approach is imperative. Establishing a Centre of Enablement can act as the lighthouse, guiding organisations in their journey to derive unparalleled value from AI.

Opinions are my own