The Year to Embed AI for Business Success

A few weeks into my role as CRO and GM of the Americas at Noogata, the excitement, challenges, and learnings aren’t slowing down! A big part of my enjoyment of this role is because, as I knew when I joined, Noogata is transforming how people in positions like mine (sales, marketing, operations, finance, and even HR)  access, analyze, and leverage data.

There are some clear trends in AI and digitalization that will change the way we work. For me, the three most notable ones going into 2022 are: 

  1. The rise of predictive analytics: predictive analytics leverage the mountains of data available today - an enterprise’s own data, third-party market data, social media data, and other disparate data sources - all to forecast and identify opportunities or threats in the future. Today, with the developments in data management and modeling methodologies, including AI, predictive analytics is becoming a powerful tool for decision-makers, Allowing enterprises to head threats off before they happen and, more importantly, identify ways to serve the customer better and increase revenues. 

  2. AI is evolving, but humans are still crucial: We’ve all seen the movie - robots save the world. (Or robots destroy the world.) Either way, those movies focus on AI replacing and even surpassing humans. In the real world, while we see huge leaps in the use of AI, its real power can only be leveraged when combined with human intelligence, reasoning, and subject matter expertise. Noogata’s AI blocks are transformational for our customers. But they’re tools that nonetheless rely on our customers’ business users and data analysts applying them effectively to their own domains and using their expertise to interpret the recommendations and craft the best course of action.

  3. Self-Service analytics will become the norm - AI is increasingly integrated into enterprises and accepted as a business differentiator, crucial to business success. The key is finding ways to make it accessible across organizations and not just the specialized data scientists. The demand for fact-based daily decision-making is pushing companies to search for self-service data analytics solutions that are user-friendly, scalable, and easily integrated. We see this across industry sectors and within business units, particularly in consumer goods/retail, technology firms, and financial services where the data volume is already high, and parsing this data is a complex, time-consuming manual process that is often error-prone and inaccurate.

    Not all business professionals are data-savvy, and most do not have the expertise required to design and build their machine learning / AI models, even with auto-ML platforms. True self-service data analytics solutions need to allow those without a technical background or in-depth knowledge of data analytics to access data and leverage AI independently. In 2022, there will be an increase in companies adopting truly self-service analytics tools that create more efficiencies, cut costs, lead to better decision making, and ultimately, increased profits.

As we go into 2022, none of these things are slowing down. We’re looking forward to building yet more blocks, working with more customers, and continuing to learn from partners, clients, and the market. What is central for us is that everything we do continues to be designed around transforming business processes and decision-making by making AI accessible to drive business impact.