Technology trends in 2020 - the barriers are falling.
There has never been a better time to start adopting new technology into your business. However, you must take the proper steps to do it successfully - focus is a must, as is learning new skill sets.
This of course sounds obvious, but a surprising number of businesses spread themselves too thin across too many technologies. Or they have found that skills are lacking, policies and methodologies are out of date, and work practices cannot keep up.
According to Daryl Plummer, Chief of research at Gartner, it's all beginning to change: "The barriers are beginning to fall. As technology matures and the skills and ideas for implementing it begin to grow, it becomes easier to locate a point to "techquilibrium," where digital needs balance with traditional business requirements. At this point of balance, organisations benefit from the use of technologies to solve real-world problems".
How are emerging technologies moving past barriers to widespread adoption at scale?
Focus is once again, the keyword when it comes to achieving technological maturity. An organisation must have a clear vision of how to use technology. With this firmly in mind, it won't matter how different a piece of technology is, you can overcome other issues such as a lack of skills or business politics.
The last three years have seen a boom in AI experimentation, and as a result, the number of vendors has risen dramatically. Where an organisation's AI project was subject to intimidating teams of data scientists and AI experts, vendors now offer practical easy-to-use cloud-based AI solutions. What was very time consuming and highly costly, is now becoming an almost turnkey industry offering use-case-focused solutions. Gartner predicts that by 2023, 84% of AI solution vendors will focus on concrete domains and industry verticals.
As cloud computing continues to grow in popularity and IT budget spending, so does the responsibilities that come with it. With so much as risk, the pressure from external and internal stakeholders, including industry regulators and politicians, can be daunting. Businesses that implement this technology need to be agile and able to respond to any resulting changes. Gartner predicts that through 2022, insufficient cloud infrastructure as a service skills will delay half of enterprise IT organisations' migration to the cloud by two years or more.
As new technologies continue to emerge and disrupt the market, they appear attractive and exciting for your business model, but pro
duct managers should be wary. Understanding the potential challenges and adjustments required as they mature is critical. Gartner predicts that through 2023, business issues will have stopped more blockchain projects than technology readiness.
How are approaches to digital transformation changing across multiple technology areas?
Digital transformation happens at very different levels of maturity for various organisations. Developing plans and strategies to deal with issues surrounding digital ethics, digital product production and digital operations can take time. A willingness to change approach multiple times is a must to achieve success.
As a whole, customer dissatisfaction, erosion of trust and privacy invasion continue to increase between customers and organisations, and even devices. As a result, ongoing adjustments to privacy and protection laws require businesses to adapt to stay compliant. Therefore, organisations that show a proactive approach to privacy and data are seeing more significant levels of trust from customers and industry leaders. Gartner predicts that before year-end 2023, more than 80% of companies worldwide will be facing at least one privacy-focused data protection regulation.
The impact of digital technologies on oil and gas operations and business conduct is growing. By offering superior business outcomes, maturing technologies are changing the industry as a whole. But to achieve these outcomes, companies must substantially remake IT and enterprise operating models. Gartner predicts that by 2022, over 50% of central IT budgets within oil and gas companies will be dedicated to finding digital products rather than IT projects.
How are employee experiences changing the expectations and processes of work?
As the workplace evolves, it seems only fitting that employees do too. But with the rapid pace that technology is advancing, it can be a struggle to keep up - both through employee actions and educational processes.
In educational institutions, this often results in pressure to streamline these changes and become more agile with their offerings. In contrast, non-educational work environments, the race to keep up with technology is only matched by the race to maintain ethical standards for its use.
The impact of automation and artificial and augmented intelligence on the world of work cannot be overstated, and workers continuously need to upskill to keep up. While some workers are facing the reality of partial replacement through technology or their position now require the use of new technologies or equipment. Gartner predicts that by 2024, the decreasing half-life of skills will force 50% of higher education institutions to adopt a pace-layering approach to course creation for 100% of the course catalogue.
In the digital workplace, everyday tools are evolving faster than ever. Technology is bringing new ways to create, collaborate, analyse and consume, and a majority of it is cloud-based. Then looking at AI, most only see ground-breaking uses such as music composition or deepfake video. But, it's infiltrating nearly all facets of a workplace without many realising it. By 2024, Gartner predicts that "everyday AI" will be essential but largely invisible in daily work activities.
While AI's explosion into the workplace is quite profound, it isn't always successful. A lot of enterprises making ventures into AI see positive results, but there are also a lot of mistakes. Success comes from practical applications and ensuring there are trust and understanding among stakeholders and employees alike. Investment in responsible and explainable AI is a must. Gartner predicts that by 2023, all personnel hired for AI development and training work will have to demonstrate expertise in responsible development for AI.