The field of data analytics & AI has matured greatly during the last decade. Organisations have made significant investments in new technical infrastructure, architecture and employee competence to position themselves to drive value through data collection and analytics. Many have experimented with new technologies and run machine learning and AI projects. The question is: how do you go from experimenting with AI to scaling it to become an important business value driver?

Through working with customers in different industries and of different digital maturity levels, we have identified several criteria that often cause AI initiatives to fail to deliver the…


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In times when speed of service has become critical and the concept of “normal business hours” has changed, we are becoming more comfortable to converse with technology like Chatbots to get our problems solved on our own terms. While some companies barely deliver a successful proof-of-concept, other companies build Chatbots that handle thousands of customer inquiries while delivering great customer experience.

Why do some companies fail to implement new technologies while others manage to transform their customer service and sustain high customer satisfaction?


It is undeniable that acceleration in technology requires firms to revisit the core of their business. Success stories enabled by data analytics and machine learning are becoming public at accelerating pace as firms try to position themselves as digital leaders. This creates urgency to evaluate automation as a new source of growth across all industries. However, companies that rush into sophisticated artificial intelligence before getting control of their data and setup structured analytics might end up paralyzed.

How NOT to hire your first Data Scientist

Let´s outline a typical bad scenario. Company executives want to boost their business with machine learning. They hire a data scientist, often a…


It´s been almost two years since I worked on a Lean Startup project to help a company identify industry challenges and capture new business opportunities in the Norwegian real estate market. The project has now become a technology startup of its own. Alva uses machine learning to create efficiency in the market. Alva is often referred to as the company challenging status quo and impacting the future of the industry.

Lean Startup is a wonderful methodology providing a structure one can follow to gain maximum insight in minimum time. However, real life is more complex and messy than the clear…


A study done by McKinsey Global Institute shows that data driven organizations are:

23 times more likely to acquire customers

6 times as likely to retain those customers and

19 times as likely to be profitable as a result

These numbers can be both inspiring and chilling depending on the data maturity state of your company. The truth is that most of the companies have more data than they know or more precisely — than they know what to do with. Many are in fact overwhelmed with data and are often confused by what defines being data-driven.

A company is…


The two most important words for the future of businesses happen to also be the two of the most hype words at the moment: data and artificial intelligence. Research done by Narrative Science shows that 62 per cent of organizations will be using Artificial Intelligence by 2018. The number is way higher for startups: many of the tech-startups, regardless of industry, have business models based on identifying a problem and applying some sort of artificial intelligence technology to solve it.

The number of companies that brand themselves as artificial intelligence companies has exploded lately — it is clear that using…

Julija Pauriene

Head of Artificial Intelligence in Avo Consulting

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