Bridging the Gap between AI deployments and ROI: DataRobot Acquires Boston Consulting Group’s SOURCE AI

DataRobot and BCG announce a strategic partnership to address the growing gap between AI deployment obtaining successful value from AI deployments.

Gradually but steadily, Artificial Intelligence (AI) projects have now shifted from whiteboards to production. AI is a transformative technology with the potential to boost revenues with improved automation, productivity and effectiveness as well as to aid the process of making impactful business decisions.

Sylvain Duranton, the Global Leader of BCG GAMMA, BCG’s data science division saysOpens a new window , “In today’s world, AI is a critical and strategic business opportunity. Companies that remain resilient and competitive must have the ability to successfully build and manage machine learning models.”

A large part of the tech industry and researchers are involved in building successful machine learning (ML) models but some of the tricky questions that surround AI adoption include: how are businesses planning to optimize business outcomes from ML models? What data will be used to power the AI systems? Some of the pain pointsOpens a new window that enterprises face during AI workload deployment are poor data volume and quality, and the skill gap for advanced data management.

With a view to plugging some of these gaps and drive AI deployment and adoption, enterprise AI company DataRobot announced a strategic partnership with Boston Consulting Group (BCG), and even acquired BCG’s booming AI platform, SOURCE AI.

Who is DataRobot?

According to IDCOpens a new window , spending on AI systems is expected to reach $97.9 billion in 2023, which indicates widespread AI adoption. Gartner reportsOpens a new window that by 2024, 50% of AI investments will be quantified and linked to specific key performance indicators to measure return on investment (ROI). Working on similar lines, Boston-based company DataRobot delivers ROI enablement services and an end-to-end automation platform to build, deploy, and manage accurate ML models. This enables businesses to transform their data into value and optimize performance. In fact with DataRobot, businesses can deploy a real-time predictive analytics service powered by an accurate ML model. Recently the company launched the DataRobot CommunityOpens a new window for data scientists and AI contributors. Igor Taber, Senior Vice President of Corporate Development, Partnerships, and Strategy at DataRobot explainsOpens a new window , “DataRobot abstracts the underlying complexity, so we can shrink the time to production and see value from what could be years into weeks.”

B2B influencer Jay Palter adds that skills, culture and resources are the prerequisites for a successful AI adoption.

The prerequisites to #AIOpens a new window deployment in business
by @DanFagellaOpens a new window via @newrulesinvestOpens a new window pic.twitter.com/6RhVa6GvA2Opens a new window

— Jay Palter (@jaypalter) June 8, 2020Opens a new window

What Does This Alliance Mean?

As AI is a competitive market, the partnership will help companies drive greater value from their AI projects, addressing and attempting to eliminate the challenges around AI. In this context, a surveyOpens a new window conducted by MIT and BCG revealed that 40% of organizations making significant investments in AI do not report business profits from AI. Solving these challenges, the alliance will coalesce BCG’s domain experts with DataRobot’s enterprise AI platform and bridge the gap between AI deployments and ROI to build industrial-grade AI solutions.

Along the lines of AI deployment challenges, Paul Hahn, AI and Analytics Marketing Leader at HPE shares in his blogOpens a new window , “The process of building and deploying of AI solutions in the cloud, multi-cloud, or edge computing environments can be daunting. Operationalizing these AI solutions as they move from pilot to production at scale. Doing so quickly and consistently can be even more challenging. Each use case has its own specific AI applications (e.g. image recognition vs. speech analytics), solution components, and partner ecosystem with different technology, data, security, and operational requirements.”

Moreover, the decision to acquire BCG’s AI platform, SOURCE AI, materialized due to the platform’s unique ability to offer data scientists restriction-free ways to write code. With SOURCE AI, DataRobot plans to deliver model experimentation, training, and production model management and deployment.

Jeremy Achin, the CEO, and co-founder of DataRobot says, “We’ve been impressed with what the SOURCE AI team has been able to achieve and look forward to tapping their expertise to further innovate at DataRobot.”

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