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How DataRobot Can Automate Your AI Development

AI is undoubtedly the hottest trend right now, and many businesses struggle to understand how to get started with their AI development. Many companies lack the skills needed, and the severe global shortage of AI experts doesn’t make things easier.

This is why a new sub-field of AI – called AutoML – is gathering a lot of interest. Essentially, it is about using AI to auto-generate AI.

I got the opportunity to interview Bo Erlandsson, the Nordic Sales Director of DataRobot, a company offering AutoML solutions. He has a background in technology organisations like Telelogic, IBM, Affecto, and most recently Informatica. He joined DataRobot in January 2019 as the Regional Director of Sales in the Nordics.

As such he is responsible for growing DataRobot’s business in the Nordic countries, advising organisations on how to build AI business cases and successfully manage data science projects. 

Now, over to the interview!

Bo Erlandsson, Nordic Sales Director of DataRobot

What is Your Company’s Background?

Today, with the advent of AI and machine learning, businesses are finding new ways to manage and leverage insights from their enormous glut of data.

DataRobot was founded in 2012 by two data scientists, Jeremy Achin and Tom de Godoy, who recognized that there wouldn’t be enough data scientists to meet this demand for AI and machine learning.

We envision a world where every business successfully implements AI. 

DataRobot was founded with a mission to teach the machines to do much of the work for a data scientist, and its technology automates the complex and repetitive tasks to help companies be more strategic, productive, and competitive. 

To do this, the company paired knowledge and best practices from some of the top data scientists with state-of-the-art technology. Alongside our technology, DataRobot has a proven track record of partnering with companies intent on transforming themselves with AI.

We envision a world where every business successfully implements AI. 

What Problem Does DataRobot Solve?

There is a tremendous shortage of data scientists in the market. Using automation, DataRobot puts the ability to create AI into the hands of more users and turns data into value. 

What is a Citizen Data Scientist?

Citizen data scientists, a term coined by Gartner, refers to an advanced data analytics professional or data professional that needs or wants to implement machine learning technology.

Organizations of all sizes across industries strive to be more data-driven, but with a worldwide shortage of trained data scientists, businesses are empowering their data analytics professionals and other domain information experts with the tools and support they need to become citizen data scientists.

Citizen data scientists work in tandem with data scientists in most artificial intelligence (AI)-driven organizations on projects that require detailed business expertise.

This allows traditionally educated data scientists to focus on more complex projects that impact the entire organization rather than the KPIs of one specific department.

Gartner predicts that the amount of advanced analysis and business value produced by citizen data scientists will surpass that of data scientists as soon as 2019.

Data analytics professionals typically focus on finding trends in data about events that have already happened (descriptive analytics) and express their results in dashboards, static reports, and graphs.

Now, however, citizen data scientists, software engineers, data engineers, and AI engineers have powerful tools that allow them to solve business problems using data with greater depth and breadth than their data analytics professional peers.

They can build models that recommend a next best course of action, identify prospects most likely to buy a product, determine which loans are most likely to default, and more.

Their influence is so significant that Gartner predicts that the amount of advanced analysis and business value produced by citizen data scientists will surpass that of data scientists as soon as 2019.

What Does DataRobot do, and why is it Important to Your Customers?

Our platform lets you accelerate your AI success with cutting-edge machine learning and the team you have in place today.

By making the production of AI efficient through unprecedented levels of automation, DataRobot dramatically expands the pool of people who can create AI and drastically increases demand and adoption.

We strive to automate every aspect of AI from end to end: from AI asset management to data preparation for AI and machine learning and through model creation, deployment, and management.

PWC estimates AI could contribute up to $15.7 trillion to the global economy in 2030

Our platform and partnership unify disjointed languages, tools and teams. By pairing customer success with the ability to solve real-world enterprise business problems, we help our customers automate the introduction and deployment of AI.

Every business process and application will be powered by AI in the future, and companies capitalizing on our automation via our Enterprise AI platform build major competitive advantage, forcing their competition to follow.

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DataRobot provides a clear roadmap for your team to build an AI-driven enterprise, no matter where you are in your journey.

DataRobot has not only invented automated machine learning technology, but is also approaching AI adoption and success in a way that helps guarantee maximum impact.

Our unique end-to-end solution is helping companies use their data to solve challenges in ways that weren’t possible — and that directly impacts their bottom line.

We strive to automate every aspect of AI from end to end

Our most successful engagements are when data scientists in a company work together with some non data scientists (BI analysts, data analysts, software engineers, etc.) — what we call the “AI-Driven Enterprise.”

Alongside our technology and approach, we have a proven track record of partnering with companies intent on transforming themselves into AI-driven enterprises.

Stakeholders learn how to create an AI Roadmap at DataRobot University while collaborating with Customer Facing Data Scientists from our AI Success team during AI Ideation Workshops and impactful use cases to make their AI vision a reality. 

How Does DataRobot use AI?

DataRobot’s technology puts the power of machine learning into the hands of any business user, automating the data science workflow and offering pre-packaged expertise that enables user to build and deploy the most accurate predictive models in minutes.

We strive to automate every aspect of AI from end to end: from AI asset management to data prep for AI and machine learning and through model creation, deployment, and management. 

In Your Mind, What is the Future of AI in Business ?

It’s not a secret that AI will soon be a part of every business application and process. PWC estimates AI could contribute up to $15.7 trillion to the global economy in 2030, more than the current output of China and India combined. Those that don’t take advantage of AI will be left behind. 

In the face of this enormous growth potential, customers face multiple obstacles to capitalize on the opportunity. A tremendous shortage of data scientists exists in the market today that will remain for years ahead.  

It’s not a secret that AI will soon be a part of every business application and process

A 344% increase in demand for data scientists has been seen from 2013 to 2019 and in the past year demand has increased 29% while supply of talent grew by just 14%. In 2018, more than 150,000 data scientists were needed by U.S. businesses.

Beyond that problem, companies wanting to adopt AI face internal challenges: up to 12 disjointed languages that can be used, 7 disjointed data science tools typically used in an organization today, and 5 disjointed technical and business teams.

The huge majority of AI models today fail to ever make it into production.

Do You Think AI Will Take Our Jobs?

No. At DataRobot, we believe AI will create jobs, not take them. Other organizations support this belief. In fact, a recent study by Gartner concluded that AI will create 2.3 million jobs over the next two years, with a net increase of half a million jobs.

At DataRobot, we believe AI will create jobs, not take them. Other organizations support this belief.

The rise of automation has certainly allowed machines to make processes that used to be cumbersome more efficient. In turn, it has augmented the work that humans are doing.

Humans, on the other hand, are strongest at communication and engagement, common sense, creativity, and empathy — areas machines and AI do not excel at.

My colleague Colin Priest summed it up well in a recent blog post: “The AI revolution will free up humans to be more human. It will take away the mundane and procedural and empower humans to be creative and social.” 

In this interview, Bo Erlandsson gave an interesting view into how tool automation can make AI development a lot easier. DataRobot is a great example of the tools we are likely going to use everywhere in a not-too-distant future.