Business information

AI and Data This Year: Bigger, Bolder, and Business-focused

When “The matrixA movie first released in 1999, it showed us an extreme version of artificial intelligence and the power of data that in many ways seemed impossible. Over 20 years later, the latest installment has been released in a world where the perception and adoption of AI and data has dramatically changed.

In 2022, AI and data are no longer “goodies” or unachievable ambitions. For years, organizations have accepted the realization that each of these capabilities is essential to gaining an advantage and growing – and the evidence is clear. Consumers are increasingly comfortable and confident with AI-enabled interactions, companies are pushing back common barriers to scale their AI programs, and companies are abandoning intuition and intuition and relying entirely on data-driven decision making.

With several high-priority use cases creating top-notch adoption opportunities, here are four AI and data trends I expect to see take shape this year:

1. Collaborative data ecosystems will be a top priority for companies

In 2022, it is critical that businesses do more than just extract information from data generated within their own organizations. A key differentiator can come from working with partners and suppliers. Research published in 2021 shows that organizations that capture additional information from data owned by companies in their ecosystems have twice the market capitalization. Such data sharing can also lead organizations to partner on new products, services and experiences.

2. Data transformation is not the end in itself

Data itself matters, but in 2022 the focus will be on leveraging data to solve business problems. The time for proofs of concept is over. As data and AI commitments become larger, more strategic, and more critical, companies need to adapt their roadmaps to support overall business goals, with a particular focus on leveraging data. and AI. Organizations have a lot of untapped ROI to exploit in this area this year and in the years to come – as alone 16% of organizations currently master both data and AI at scale. To move to the next level of business-driven transformation in 2022, business leaders, including CXOs, need to become more involved in data, analytics, AI and data governance programs, which is still not the case in most organizations. Breaking down these business and IT silos may seem like a step forward, but companies need to tie them more tightly to maximize the potential benefits of each.

3. AI will make every supply chain efficient

The disruption caused by the pandemic has forced companies in nearly every industry to tackle supply chain challenges and prioritize resilience. To achieve this, supply chains must be AI-enabled in all process areas and leverage data ecosystems built through collaboration of partners. Historical data, as well as existing supply chain planning approaches and models, will be less relevant in 2022 due to changes in consumer demand and purchasing habits in recent years. From supply planning to demand planning, raw material sourcing and digital manufacturing, supply chains in 2022 need to be redesigned, AI-enabled and, most importantly, sustainable.

4. A relentless focus on “everything related to talent”

The landscapes of AI and data are constantly evolving – and one of the big consequences is an ever-changing talent market. In 2022, organizations seeking AI and data talent must invest in world-class recruitment and retention initiatives to tackle the Great Resignation, promoting inclusiveness and a culture of learning and organic growth. throughout life. In addition to their day-to-day roles, employees working in these fields look for opportunities to work on useful and rewarding projects in areas such as environmental sustainability – and companies need to ensure that they are creating pathways for their talents. AI and data get them. experiences. This is especially true for industry organizations, which may face increased competition from large, tech-driven companies when looking to recruit and retain team members with AI and data skills.