The title of this column series is "AI in Action," and there has indeed been a lot of action over the past year. Judging from the 11th annual NewVantage Partners survey of senior data and analytics executives, some trends are moving in the right direction. For example, more companies are creating senior roles to focus on data and analytics. The chief data officer role has quickly become much more common over time and across more industries; in the survey, 83% of companies have appointed a CDO or chief data and analytics officer (CDAO). An increasing number of companies (69% in this year's survey) are officially incorporating analytics and AI into the CDO role, and we think that's a good idea.

Lexy Kassan is a thought leader for doing good things with data. She oversees and guides customers in transforming their data culture to best position for creating value out of technology and analytics investments. She has seen first-hand the power of empowering people with the right tools and just enough governance to optimise processes and achieve business outcomes. Data has an increasing role to play in our lives and societies and Lexy is actively involved in shaping that role. She is a thought leader in data and AI ethics, Founder and Host of the Data Science Ethics Podcast, and a frequent speaker and guest lecturer on the topic at institutions around the world.

There's been a renewed focus on digital transformation (opens in new tab) over the past two years, driven in part by the pandemic. Whilst it was already on many organizations' agendas and a central component of their business strategy, the pandemic led to a significant need to speed up the digital transformation that was underway. Craig Stewart is CTO at SnapLogic (opens in new tab). Accompanying this shift, there has also been the growing need for better data (opens in new tab) literacy across all employees (opens in new tab). However, the importance that businesses place on data literacy awareness and training, and the benefits that greater data literacy can bring, often fades into the background when introducing new technologies or initiatives.

WIRE)--Alation Inc., the leader in enterprise data intelligence solutions, today announced the acquisition of Lyngo Analytics, a Los Altos, Calif.-based data insights company. The acquisition will elevate the business user experience within the data catalog, scale data intelligence, and help organizations drive data culture. Lyngo Analytics CEO and co-founder Jennifer Wu and CTO and co-founder Joachim Rahmfeld will join the company. Lyngo Analytics uses a natural language interface to empower users to discover data and insights by asking questions using simple, familiar business terms. Alation offers the most intelligent and user-friendly machine-learning data catalog on the market.

The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. Alation today released its latest State of Data Culture report, which focused on how ignoring data can lead to major business missteps. The report highlights that 97% of data leaders say their companies have suffered the consequences of ignoring data, either missing out on new revenue opportunities, poorly forecasting performance, or making bad investments. "The organizations that learn from data faster understand their customers, innovate, and sense markets quicker and more clearly than others," Alation cofounder and CEO Satyen Sangani said in a press release. "Companies that invest in data and build a culture of data literacy do well. Companies need to transform how they make decisions and how they work to incorporate data into everything they do. They have to build a data culture."

Accenture interviewed 100 C-suite executives in wealth management last year and found many are skeptical of artificial intelligence. Eighty-five percent said its impact is "more hype than reality for businesses today." Still, 60% of them are already using AI in their organizations and they're doing it so well that other industries could learn from them, according to a new report. "Understanding the application of AI to business requires an understanding of context -- strategy, customers, company culture, and so forth. One application worthy of study across organizations is wealth management," Babson College professor Tom Davenport and NewVantage Partners founder and CEO Randy Bean, wrote in the MIT Sloan Management Review.

While many companies across a range of industries have placed artificial intelligence (AI) and machine learning (ML) at the heart of their growth strategy, most do not feel they are in a position to successfully harness its power. The major reason for this is because many Big Data projects lack a mature approach to getting the best out of AI and ML deployments. According to a 2021 Databricks and MIT Technology Review Insights survey, companies' most important business objectives for their enterprise data strategy over the next two years are expanding sales and service channels ( cited by 45 percent of respondents), better operational efficiency (43 percent) and improving innovation and reducing time to market (42 percent). It's great to have these objectives, but are businesses equipped to execute them? According to Gartner, 85 percent of big data projects fail, and according to the MIT Report only 13 percent of companies excel at implementing their data strategy with measurable results. When asking "low-achievers" (organizations having difficulties with their data strategy initiatives) what their main barriers are, the feedback highlighted limited scalability of their data management platform, difficulties in facilitating collaboration and slow processing of large data volumes.

Artificial Intelligence (AI) and Machine Learning (ML) have burst into the spotlight in recent years getting attention from businesses and all levels of society. Awareness of AI has drastically increased as people become more familiar with how the tech giants are using data to enhance their products and create better solutions. The market is opening up to more AI-infused products, and the public are regularly interacting with AI as it slips into their day-to-day lives through smartphones and virtual assistants. Many companies who are taking the plunge with AI initiatives are not coming out on top, and this is usually because they were not AI Ready when they thought they were. So what does it mean for a business to be AI Ready?

In order to compete in the new digital economy, businesses must become increasingly data-driven. Few executives would dispute this objective. Recent events, including the global outbreak of COVID-19, have underscored the critical importance of having reliable data to inform organizational decision-making. Yet companies continue to struggle to operate in a data-driven manner. Even though we are now decades into the age of competing with data, a 2020 NewVantage Partners survey of C-suite executives representing more than 70 Fortune 1000 companies found that only 37.8% of companies have created a data-driven organization.

Artificial Intelligence has evolved from being a buzz word to a reality today. Companies with expertise in Machine learning systems are looking to graduate to Artificial Intelligence-based technologies. The enterprises that do not yet have a machine learning culture are trying to devise a strategy to put one in place. Amidst this hype and the fear of being left behind, how would you embark upon an AI strategy in your company? This appears to be a recurring and common question today.