Cybit Appoints Marc Pawson as New Sales Director
Cybit, a leading provider of data intelligence and AI-driven technology solutions, today announces the appointment of Marc Pawson as its new Sales Director.
Read articleBuilding a Strong Foundation: Key Steps for Businesses to Unlock the Full Potential of AI
Rob Hankin, Chief Technology Officer at Cybit
If you’ve been monitoring the news, you will have seen that Northumberland County Council recently approved planning permission for a giant AI and cloud computing data centre. Costing a staggering £10 billion, the development is predicted to create hundreds of jobs and build a foundation for a tech hub in the local area.
This news story is just one example of the investment taking place across the UK to build a robust and scalable infrastructure that supports the growing demands of AI and cloud computing. In fact, Gartner predicted that investment in IT services related to AI in Europe will grow from $78 billion in 2024 to $94 billion in 2025.
The UK is rapidly emerging as a global leader in AI innovation, with British companies looking to become more data-driven in their operations. Data is increasingly being seen as a valuable asset to inform strategic decisions and drive innovation across different markets. But the majority of UK businesses need to take a step back and get their foundations in place before they can fully harness the potential of AI and the advantages it offers.
Step 1
Ensuring Data Quality
AI systems thrive on data, but it’s vital that business data is accurate, consistent and clean in order for the technology to function effectively and generate accurate insights. Investing in data management practices, including data cleaning and validation, will be key, especially when it is integrated across all departments. Companies will also need to consider data bias as AI models inherit biases from historical data. They will need to actively identify and mitigate biases, ensuring that the data used to train the models is diverse and representative.
Step 2
Investing in Data Infrastructure
Once the data quality has been established, businesses will need to create a centralised place to store data, whilst ensuring that it is easily accessible for everyone in the company. Whilst this ensures that AI systems have a broad and unified data set to work from, it also means that the system is scalable to meet the changing needs of the organisation. Businesses need to have scalable data infrastructure that is capable of handling large volumes of data seamlessly.
Step 3
Building Data Literacy
Getting employees on board is the next stage in building a foundation for AI-powered solutions. Equipping teams with the necessary skills through training and development can help them build an understanding of the tools available and how this will impact their day-to-day role and responsibilities. Over time, businesses will be able to foster a culture of decision-making and innovation, encouraging teams to embrace technological advancements and data-driven insights.
Step 4
Setting Clear Objectives
Having a clear understanding of how AI will contribute to the overall business objectives, whether that is improving operational efficiency, enhancing customer experience or strengthening security best practices. Key performance indicators (KPIs) will also be helpful in tracking AI initiatives and measuring their impact on company outcomes. Not only does this help justify investment in the C-suite, but it can help identify areas for improvement and guide future strategies.
Step 5
Establish Ethical Guidelines
Developing ethical guidelines for AI is the next step, covering transparency, accountability and fairness. This will ensure all decisions are made ethically and potential issues can be addressed on time. ESG also comes into play here, as businesses need to adopt a balanced approach that incorporates sustainable practices and responsible resource management. Focussing on sustainability throughout the AI lifecycle, from hardware selection to model deployment, is fundamental in reducing the environmental impact of AI initiatives.
Step 6
Partnering with Data & Analytics Specialists
Starting small to test and understand the technology’s potential is crucial before scaling up. Using these smaller projects to learn, iron out issues and fine-tune the approach. Partnering with companies, like Cybit, allows organisations to continuously monitor and improve solutions to ensure they remain effective.
Depending on the solution needed, organisations can achieve in-depth data exploration, effortless data prep, data warehouse automation, or cost-effective data visualisations. Alternatively, they may choose to build a full end-to-end analytics solution, from data blending and preparation all the way through to data visualisation and exploration.
The UK AI landscape holds immense promise, with the potential to drive economic growth, create high-value jobs and solidify the UK’s position as a global leader in AI innovation. However, businesses need to ensure that they have a solid foundation in place and are future-proofed to navigate the evolving technological landscape, emerging trends, and the strategic investments required to fully unlock AI’s transformative benefits.
About Rob Hankin
Rob Hankin (CTO) has 25 years of IT leadership, including a decade in a multi-national manufacturing environment. Over the past 15 years, Rob has worked with leading technologies, vendors, and distributors including Microsoft and AWS. He leads Cybit’s technology partnerships, supporting private and public sector customers across the globe. Rob’s expertise is highly valued by key industry players, where he has served on Partner Advisory Councils and Product Advisory teams. As a trusted advisor, he helps organisations from small enterprises to global industry leaders unlock opportunities through technology.
