Artificial intelligence (AI) capabilities that benefit all business areas are essential to your efficiency and future growth.
Businesses must learn and adapt AI at scale to survive this new emerging future. Creating an AI model development framework requires aligning your data strategy, business model, processes, people and systems to generate value from AI capabilities. Data Engineering, Data Science, Machine Learning, Generative AI, and Robotics have emerged as must-have components in your business. together they allow you to take Actionable Insights to the next level, by automating workflows and creating self-determining autonomous agents that work 24/7 for you and your business.
Harnessing data, building automation, and delivering personalisation on demand can all lead to long-term advantages as your business grows. Here are just some of the examples of how we are using AI to deliver value today.
| Opportunity | Example Use Cases |
|---|---|
| Generative AI Productivity | Develop a deep understanding of your audience, channel performance, and attribution. Get to the heart of the Why and the What, creating insights and allowing you to adapt in near real-time. |
| Supply Chain Optimisation | Warehouse and logistics efficiency, such as ensuring the right amount of stock is available to your partners and customers, in the right locations, is a must to maximise margins and customer experience satisfaction. |
| Qualitative Research | Develop a deep understanding of your audience, channel performance, and attribution. Get to the heart of the Why as well as the What, creating insights and allowing you to adapt in near real-time. |
| Investment Portfolio | Multi-asset portfolio creation and analysis for public and private assets. Manage workflows and tap into AI expertise for various due diligence actions and risks before making investment decisions. |
| Culture & Language | Engage global markets and employees with smart AI-powered document workflows, such as real-time translation and critical fact extraction, such as colleague sentiment. |
| Compliance Automation | Face the ever-growing global protection and privacy rules with personalized legal statements that give you GDPR, CCPA, PIPEDA, and ePrivacy Regulation compliance without expensive legal fees. |
AI Discovery
In a short discovery phase, we would gather information from stakeholders and domain experts to pinpoint the most critical and impactful use cases. By employing lean frameworks and quick interviews, teams would identify use cases, and enable the creation of an initial problem-solution map, ensuring alignment of AI efforts with business needs. The team will also identify existing data assets, explore data quality, and review the current technology infrastructure to confirm feasibility. The aim is to determine whether the organization has the right information, tools, and processes in place to support an AI solution before committing to further development.
Once the relevant use cases are mapped out, we propose design patterns based on mental models, cognitive schemas, and adaptable design principles. These patterns help guide system solutions, user experience, governance and build priorities, ensuring the AI solution remains intuitive, flexible, and responsive to changing requirements. Rapid prototypes or proof-of-concept models are then used to conduct performance evaluations, allowing the team to gauge the solution’s effectiveness and scalability in real-world conditions. By running iterative tests, measuring key performance indicators, and refining the design, the feasibility of each use case is continually assessed. This holistic and iterative approach ensures that the AI initiative moves forward with a solid foundation, minimizing risk and maximizing value within a short timeframe.
AI Solutions
These are covered in more detail in the Solutions area. The main services we offer as part of the AI Automation Agency are: Model Engineering, Prompt Engineering, Workflow Automation, Autonomous Agents, Natural Language bots, and Multi-modal/media capabilities (e.g. converting video to text or vice versa).
AI Adoption
Blending scalable technology, consumer and colleague-centric approaches to creating an AI-powered enterprise requires new skills, AI governance and a faster “self-service” approach to creating innovation opportunities. We can help you find ways to accelerate AI adoption to drive growth, profit, efficiency, and optimization across your business.
Don’t let your AI pilots fail and therefore miss out on the opportunities it can bring. Create the foundations for success, and be pragmatic yet persistent in the drive to adopt AI across the entire business. Discover new propositions through continuous proposition innovation. We have a range of approaches to help you scale AI successfully and generate increasing sources of value.
