Accelerate your transition to an AI-native organization by giving business managers the language, tools and techniques to collaborate seamlessly with technical specialists.

Delivering business impact with AI and data requires investment in specific, highly specialized technical and advanced analytics skills. But that's only half the story. It also requires deep understanding of the workings of the business and its customers, and the ability to show others in the organization how to use AI and data to make better decisions and develop more efficient processes.

As a translator, you will understand the lifecycle of designing, developing and implementing AI solutions. You will take an active role as part of a multi-disciplinary development team to design and build AI solutions. 

In order to do this, you will get a deeper understanding of the technical aspects of machine learning and AI engineering and how they are applied to solve business problems. This will allow you to effectively collaborate with specialist data scientists and AI engineers, and support their efforts through effective communication with business leadership. 

The AI-native organization requires more than technical capabilities. It needs a new kind of manager – a 'translator', who understands data and AI and can communicate fluently with business leadership and technical specialists, translating requirements and expectations to deliver high-value AI solutions with real business impact.

Understand how to use data and technology to operationalize AI:

Learn the key concepts behind AI and data transformation, and gain a clear understanding of what they can and can't (yet) achieve.

Identify value creation opportunities:

Using existing business challenges as a starting point, apply systems thinking and data analysis to identify solutions and how to deliver them.

Develop and communicate the business case:

Learn proven techniques for visualizing and presenting data, and communicating the value and impact of AI-driven solutions.

Lead AI and data teams at project and organizational level:

Act as the lynchpin between business and technical leadership teams, to ensure technical specialists are fully supported while staying aligned with business objectives.

Interpret, challenge and progress data-led analyses of AI solutions:

Steer continuous improvement of AI solutions, and scale them up to amplify impact and value across the business.

To bring real value with these machine learning technologies, you need people that connect to the business and understand business processes. People that can identify opportunities and translate them in terms of what you need from data, algorithms, and AI technology.
Sandra Oudshoff
Senior Consultant, Heineken Global Center of Excellence for Advanced Analytics
What if we could enhance collaboration between business and technical teams to accelerate and amplify your AI and data transformation...
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