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How leaders are applying AI

AI needs data, and as it gets more data from a variety of sources, it gains accuracy and efficacy.

Our customers’ most valuable use cases come when AI is applied as part of broader operational systems, such as Marketing, Finance, HR, Operations and their Supply Chains. AI leaders are therefore applying AI, across multiple functions and business units, in full integration with broader automation initiatives, data analytics or both.

Given that approach, it is no surprise that the top-three AI data-related challenges all have to do with different kinds of integration:

  • Integrating data from across the organisation and with external data
  • Integrating AI and analytics systems
  • Integrating AI with IoT and other technical/operational systems

To solve these and other challenges as you make AI operational, it is critical to realise that AI development is very different from software development and requires a different mindset, approach and tools. Whereas software development is based on rules of coding, AI model development requires a “test and learn” approach, in which the algorithms are continually learning, and the data is being refined.

AI Predictions Survey

Does applying AI give you the edge?

Artificial Intelligence (AI) is not a single technology but a set of methods, platforms and tools with sub-domains applied to countless situations. At Data Technology we like to say, “Technology is implemented. Bots are built. But AI is applied!”

Value from AI doesn’t come just from “putting it in” But AI is maturing and being embedded in enterprise systems or becoming more accessible for non-technical users giving them real-time actionable insights.

To realise value from AI and get the edge, you need to acknowledge the scope and risks specific to your organisation. Then, define the value and capabilities needed to integrate, activate, incorporate and automate your business processes whilst constantly testing model efficiency.

AI driven companies grow0fasterWith0higher profits

Your 3 Steps To AI Success

Strategy

We work intimately with our clients to understand their business problems and develop a bespoke AI strategy around their needs and capabilities.

We begin this process with out highly reviewed, free AI strategy workshop.

Solutions

Once the strategy is defined, we use our industry experience to recommend the technical solutions that supports your goals.

Our expert team will then ensure everything integrates with your existing infrastructure seamlessly

Success

Our Training and AI Success Plan is designed to make your team autonomous.

Our success team will work continuously with you to improve and identify new areas to apply AI.

The Recipe For AI Success

To succeed with AI you need three things:

01Domain expertise.

02Data Strategy & Industry Insights.

03The Right AI Technology.

This is where Data Technology comes in.

We partner with your teams of analysts and data scientists who have unparalleled domain knowledge of your business and industry to jointly apply Automated Machine Learning Platforms in a matter of days – not months and years and a fraction of the cost.

Our consultants work at the forefront of the rapidly developing AI sector, keeping customers up to speed with innovation and effectively future proofing their business. We can help you interpret the results and navigate the business change process as your company evolves from being reactive to being proactive.

Embracing Artificial Intelligence will provide you with a ruthless competitive advantage over your competitors

AI Success

Data Technology Is Trusted By Global Leaders

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AI Success Stories

  • 01 / 05

    “Work that would typically take weeks to code up, machine learning models can do in an hour. It gives us time back so we can focus on more important aspects of the business problem”
    Director of Data Science

  • 02 / 05

    “The Machine Learning models have proven to be so accurate in their real-time predictions of credit default that Harmoney has been able to improve profitability for lenders, reduce costs to borrowers, and sharpen the company’s competitive position against incumbent lenders in our market”
    Chief Data Scientist

  • 03 / 05

    “We are using Machine Learning to make some pretty huge decisions at Steward Healthcare. It’s very much a part of our growth strategy. It’s unchartered territory for healthcare”
    Executive Director

  • 04 / 05

    “Machine Learning changed the way we work. It enabled us to solve business problems in a completely different way”
    Head of Consumer Data Analytics

  • 05 / 05

    “We want to be truly customer focused with all our 16 million customers, and to do that we need to be able to predict the potential behaviour of each of them to put the right offer in front of them at the right time. Machine Learning is the only way to do this”
    Head of Data Science