2023 Predictions for Data, AI, C-Suite Leadership, and Privacy

This year has been one of rapid change around the world, with geopolitical turmoil, a challenging economic situation and the COVID-19 pandemic still affecting our daily lives. Despite these challenges, data is an area that is constantly growing – it is expected to reach more than 180 zettabytes by 2025, according to Statistical research.

As technology advances rapidly and the amount of data increases, it’s no wonder that McKinsey predicts that 2025 will be the year of “the data-driven company.” They predict that in just two years from now, data will be embedded in every decision, interaction, and process, as companies increasingly rely on data for insights and value generation. Gartner predicts further that by 2023, “optimizing IT systems for greater reliability, improving data-driven decision-making, and preserving the value integrity of production AI systems” will be key to staying strategic.

For business leaders, data is at the heart of strategic decision-making and will continue to be vital. As we look to 2023 and beyond, here are my top predictions for all things data, including artificial intelligence (AI), C-Suite leadership, and privacy.

The fundamental work behind AI

As much as we love AI, many companies have burned their fingers on huge investments in isolated use cases, without seeing large, expected returns. For example, in 2023 we will see a further shift from “AI solves all my problems; let’s just hire enough data scientists” for a more thorough approach.

AI will still be immensely valuable, but major problems are based on the foundations not being ready, with data quality more often than not the underlying issue. According to research, cleaning and transforming data can take up 80% of a data scientist’s time, leaving little for the real work around AI. More companies will realize that investing in AI is not a shortcut to bypassing 10 data maturity steps at once.

Only after data quality is prioritized and invested in can organizations leverage behavioral data and unlock the value of data that is created. Behavioral data allows companies to create data that makes sense for their specialized situation, for example with data product accelerators.

Data creation and data processing

Businesses are drowning in data these days. Gone are the times when everyone wanted to generate ‘more data’ in the first place. Making better use of data is the mantra in the future. We will see more and more organizations take a conscious approach to data creation, creating or collecting the data you really need, in a defined, aligned and agreed quality that is production-ready for business intelligence (BI) and AI use cases. This is a theme that Snowplow refers to as “Data Creation.” Of course, this means that teams need to be very specific and explicit about what data is being created, why and when.

Data contracts are an important topic to pay attention to: a technical definition of what data should look like in order to be properly validated (i.e. accepted) by the data pipelines/stack, which can be read by both humans and machines and is usually provided with API functionality. Contracts are agreements between those who “need” the data (the marketing team) and the data/IT teams. Data that has been contracted and validated will be rendered exactly the way you want and need it, saving you a huge amount of time further downstream, especially in the data warehouse or data science scenarios.

On a broader level, DataOps is emerging, aimed at reducing time-to-value in our data lifecycle. Many proven processes, best practices and technologies from IT and development teams will be applied to the data world, including enforcing interfaces, or contracts, between systems or APIs.

From observability to data lineage, agile development methods and more, there’s a lot to learn and adapt from engineering teams. When focusing on delivering insights and actionable recommendations to the business, there is an important human component. Collaboration and governance require a unique approach rather than simply copying lessons from IT.

Data ethics and AI

This also leads to the importance of AI data ethics, which is likely to gain traction in the coming years. While data ethics is not yet mainstream, it should be. With more and more technical capabilities emerging, especially in the field of AI, we need to talk more about how to use data, our algorithms and findings in an ethical way.

There is more than one story about machine learning (ML) trained models discriminating against certain groups of people. For example, because the training data already reflected some bias, algorithms denying credits based on questionable correlations, or companies sending “you are very likely pregnant” messages to customers, pushing them into a very delicate field of intimacy and privacy.

The bottom line is that conversations about data ethics and AI are essential to have. This problem is receiving more attention worldwide because more standards and frameworks are being created. For example, The Council on the Responsible Use of AI was founded, a consortium was founded in Singapore to promote the ethical use of AI and data analytics in the financial sector, and some of the largest technology companies founded The Partnership on AI.

The role of the Chief Data Officer

For years, we’ve seen a lot of isolated and technology-driven investments in data. Yet there is often no coherent data strategy that connects all data efforts. More importantly, it is critical to properly connect data strategy with business strategy and desired outcomes. Many companies will upgrade their existing strategic and operational efforts to clearly demonstrate how data helps create business value and contribute to concrete goals.

Research points to the benefits of companies having a dedicated data chief. Two-thirds of companies that have a Chief Data Officer (CDO) say they do perform better rivals in market share and data-driven innovation. 2021, Gartner estimated that less than 50% of large companies have a CDO role. However, with digitization constantly disrupting business models and technology landscapes – let alone continued investment in AI – many companies are likely to follow suit.

Whether we look at Amazon, Netflix, Meta, Apple or non-digital natives like Walmart, they are all known for their serious investments and the great benefits of deeply integrating data analytics and AI into their business operations and decision making. We expect more and more companies to create space in their C-Suite, realizing that data is so much more than their weekly PDF report.

It is fundamental to digital business, in the same way that electricity is in our modern world. Data-driven winners integrate data into all their decisions, their meetings, R&D and of course all customer facing functions. Accompanying this transformational change requires considerable commitment at the boardroom table.

Data Privacy and Compliance

One of the hot topics in Europe and beyond remains data privacy and compliance. In a research by KPMG, 86% of respondents identified data privacy as a growing concern. Whether it’s because customers are increasingly aware of how brands use their data, or because regulatory authorities are significantly increasing scrutiny and de facto bans Google Analytics in some countries, it has never been more important for organizations to consider how data compliance and ongoing data management are a critical part of their business and data strategy.

Companies need to realize that this is our new reality. Privacy rules are here to stay, no matter how detailed they look. Rather than continuing to leverage datasets to the maximum, often without proper knowledge, consent or understanding from their customers, organizations need to embrace this unique opportunity ahead of their competition.

It is an opportunity and a necessity to form a new relationship with users and customers, a relationship guided by getting something back in return for sharing private data. It will continue to play an essential role in learning what works and what doesn’t, or in making decisions across the board that support data.

Finally

The days of exhausting all possible data points are finally over. Less is more. Deliberately creating and using what you need becomes the new status quo.

Looking back at 2022, it has been a year of high innovation for organizations worldwide, despite ongoing geopolitical and economic challenges. For 2023, I predict there will be a lot of change and innovation in data, whether it’s AI, the CDO leadership position or data privacy.

Chris Lubasch is the CDO and regional VP for Germany, Austria and Switzerland (DACH region). Snowplough.