Data trends to reshape the businesses in 2022

In the past two years, every industry has witnessed various revolutionary trends, and many of them were unpredictable. So, it is quite challenging to say what the next trend would be. Though there is a constant and reliable way forward, that is the data. Data has played a vital role in identifying improvement requirements in businesses, communities, and the world. Organizations applying trusted data are well-positioned for navigating through change and setting themselves up for success in the future. Nevertheless, here are the five data trends that would reshape businesses in the year concerning artificial intelligence, workforce development, data ethics as a framework, flexible governance, and data equity.

Artificial Intelligence to enrich and empower human expertise

The golden age of data and technology is heading towards a brighter era of technological growth. Artificial intelligence (AI) technology goes on to develop: machine learning (ML) models are encrypting trillions of lines of data, natural language processing (NLP) advancements are driving towards understanding human intent, and algorithms are getting quicker. Presently, the world is witnessing simpler, repetitive tasks are automated, giving rise to new opportunities to facilitate humans to do what they do best: analyzing critically and understanding data in context. Business and IT leaders trust that investing in data and AI in the upcoming five years is critical to the future existence of their business. As per the International Data Corporation (IDC), by 2026, 60% of Indian enterprises will unite human expertise with AI, ML, natural language processing, and pattern recognition to deliver business products. All the credits go to cloud computing, where AI has become more affordable and accessible. It is leading to leading to more incredible innovation across experiences and industries. The solutions that combine different AI techniques to get better results (also known as composite AI) are added to support people.

Standardizing ethical data & AI usage crucial to organizations

Trust and transparency serve as the foundation for innovation, growth, and customer relationships more than ever. As organizations helm their ethical use responsibilities, the public will likely see more transparent AI and machine learning (ML) solutions and experiences that lift human judgment and expertise. They’ll also connect directly to business goals and workflows and mitigate related risks with explainability—including bias. Organizations would be addressing biased algorithms and data sets that can damage real people and create errors with negative, downstream risks such as “ethical debt” as technical debt. The future will witness more corporate, and government commitment and accountability for ethical, responsible data and AI use. Closer to home, the Indian government’s policy thinks tank NITI Aayog and the Centre for the Fourth Industrial Revolution have collaborated to co‑design an ethics framework to ensure the responsible use of AI within both public and private segments.

Workforce Development needs more than just data skills and tools training

Today's world is further becoming data-driven, building global demand for data skills. Data literacy is the key to discovering the value of data and technology investments in a market where data is the most significant differentiator. Of equal importance is a Data Culture. Organizations have acknowledged the requirement to foster a shared culture and mindset that values and practices using data. Organizations endow in people development to upskill the workforce; they'll team up with third-party organizations to teach and upskill. Data skills will be crucial for every role and in every workforce segment.

Flexible Governance to endure competitive and compliant

Data has enhanced its role in business success. In 2022, it is not just table stakes for success; data is the business. As organizations finance innovative AI solutions and cloud-based everything, the market for self-service and data-sharing capabilities has grown alongside data privacy and usage regulations. They must take a new data governance approach that pairs flexibility and empowerment with coordinated control. Successful organizations will adopt federated data governance techniques to innovate, compete, and keep ahead of governance and security necessities. Such an approach—that pairs centrally-defined governance standards with local domain authority—will enable organizations to tap into diverse areas of expertise by including more diverse users across the business.

Data Equity, a framework to enhance dialogue between people and institutions

Data is working as a powerful agent for change. Unfortunately, it’s still not reachable to many people and a major part of the society is not getting equal benefit of the power. For relevant, effective, and sustainable data solutions, they must be designed to collaborate with the communities they intend to represent and support. By changing the dynamic, data assists empower people and organizations to address the complex, nuanced problems most significant to them. Country-level decision-makers and healthcare authorities need data—and better usage of that data—to enrich health system resilience and response to health emergencies such as COVID-19. Hence, nonprofits, organizers, and community workers should have data as a strategic asset to build data cultures and be further data literate. Democratizing data is not only about making it public but approachable by freeing it from behind the barrier of data science expertise. It enables organizations to be reluctant to add data and analytics to their advocacy measures. Better data and data equity as a framework facilitate people to begin or reframe conversations, creating beneficial downstream effects on funding requests and policy changes. And it permits community stakeholders to directly engage with their governments and other institutions of power on a more level footing.

Conclusion

Data is present and the future to discovering stability, growth, and a force for social good. The critical component empowers an organization to make decisions, and it will also be a mandatory skillset to build future knowledge workers. The potential impact of data will get more powerful as increased automation, AI, and forecasting models support users in better anticipating and preparing for what’s ahead. Even in a crisis, those who have taken the initiative to shift to a digital-first mindset, driven by data, are better prepared to go with whatever comes next.