Supporting organisations to gain an understanding of the data, business model, and leadership challenges and opportunities presented by AI technologies.

The Awareness programme is designed to support businesses and organisations understand how to harness the capabilities of AI technologies and improve their knowledge and intention to adopt.

Delivered in a peer-to-peer action learning environment, the programme allows participants to discuss the challenges posed by AI in specific sectors and explore practical approaches to harness these
technologies to boost business productivity and market competitiveness, focusing on:

1. AI digital data literacy (within the organisation and its people). Improving data literacy within the organisation is crucial for sensing and seizing opportunities and challenges, improving both strategic and operational planning.
2. AI digital leadership. Improve the capabilities of your leadership team to data-driven drive change in the organisation through AI technologies.
3. AI business or service model development. Explore the impact of AI and automation on the future of your business or service delivery model, to meet client demand, improve productivity and remain competitive.

Supporting businesses and organisations to transform their business and service delivery models to harness AI for growth and productivity.

AI-enabled business models. AI is having a transformative effect (some positive, some negative) on most industry sectors, and this presents significant data literacy, business model, and leadership challenges for particularly small and medium sized businesses. We have made some recent adaptations to the Innovation Sprint to help organisations strategically plan for significant AI-enabled transformation of the business and service models. This is proving an increasing relevant dimension of our support. A full, dedicated end-to-end ‘AI business model innovation’ programme is currently in development at Edge Hill. 

Helping businesses and organisations in key phases of new AI product development

Feasibility studies

To determine if an AI product is viable it’s essential to assess its technical, financial, and operational feasibility. Our support can cover conducting a technical feasibility study to ensure the availability of necessary data, algorithms, and infrastructure; performing market research to validate demand for the product; analysing costs, resource needs, potential ROI, and associated risks; or evaluating operational feasibility, considering factors like team expertise, infrastructure, and project timelines.

Together, these steps provide a comprehensive understanding of the product’s potential for successful implementation and scalability.

Developing a Proof of Concept

To validate the technical feasibility of an AI product’s core functionality, our support can focus on building a limited-scope AI model to test essential algorithms or methodologies, such as machine learning or deep learning. This Proof of Concept (PoC) is conducted with a subset of data within a controlled environment, allowing us to evaluate the model’s performance in terms of accuracy and speed while identifying any technical challenges or limitations. The deliverables from this stage include detailed PoC results demonstrating the AI model’s viability and recommendations for next steps, which may involve adjustments or advancing to the prototype phase.

Developing a Product Prototype

To demonstrate the product’s core features and user experience, our support can help develop a functional prototype that highlights key product capabilities. This process involves building an interactive version of the product, designing and implementing a user interface (UI) for testing, and integrating the AI model with essential backend systems for real-time or near-real-time performance. We can then help gather initial feedback from stakeholders or selected users to refine the product further. The deliverables from this stage include a working prototype ready for internal or external testing, alongside user feedback and an iteration plan for ongoing improvements.