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IT Executives Discuss Strategies for Addressing Digital and Cyber Trends in 2023

The new year has begun, bringing with it solutions and challenges that will affect all industries. Businesses and analysts alike are sharpening their focus on what lies ahead as the floundering economy continues to hopscotch around broken supply chains and worsening cybersecurity breakdowns.

IT Executives Discuss Strategies For Addressing Digital And Cyber Trends In 2023

 

TechNewsWorld interviewed IT executives to get their predictions for 2023. They provided insightful writings on the wall about what to expect in the future.

 

One of the most pressing issues is the need for more effective cyber defences to protect the cyber infrastructure. Aside from politics, Executive Order 14028, issued in May 2021, outlined the priorities. The order issued by President Biden requires agencies to improve their security in order to ensure the integrity of the software supply chain.

 

“Software vendors can no longer hide their flaws, and software users can no longer avoid their responsibilities if they choose to deploy something inappropriate,” Jon Geater, chief product and technology officer at RKVST, a SaaS platform for tracking supply chain issues, told TechNewsWorld.

 

He believes that, while there is still work to be done, the digital supply chain is finally being recognised as being as important as the physical one. Geater also believes that it is critical for suppliers to provide quality and for consumers to control their own risk.

 

“Companies and governments all over the world are realising that the software they use to run their enterprise operations and power the hardware and software solutions they use and deliver to customers represents a significant risk.”

 

Priority is given to core technologies.The current political and macroeconomic situations are worse than most people predicted, which is chilling innovation, according to Geater.



People will be more concerned with cost-cutting and efficiency. However, the importance of the core technologies being developed will not be diminished.

 

“However, it shifts the focus from new use cases, such as active cyber defence, to improving existing use cases, such as more efficient audits,” he explained.

 

According to Geater, most supply chain problems stem from errors or oversights in the supply chain itself, which exposes the target to traditional cyberattacks.

 

“It’s a minor distinction, but it’s significant. “I believe that the majority of discoveries resulting from improvements in supply chain visibility [in 2023] will demonstrate that most threats are the result of error, not malice,” Geater said.

 

According to Moses Guttmann, CEO and co-founder of ClearML, an MLOps platform, the new year will place a renewed emphasis on machine learning operations (MLOps). It is critical to assess how machine learning has evolved as a discipline, technology, and industry.

 

He anticipates that spending on artificial intelligence and machine learning will continue to rise as businesses seek ways to optimise rising investments and ensure value, particularly in a challenging macroeconomic environment.

 

“Many top technology companies have announced layoffs in the second half of 2022. “It’s unlikely that any of these companies are laying off their most talented machine learning employees,” Guttmann told TechNewsWorld.

 

To fill the void left by fewer people on highly technical teams, companies will have to rely even more on automation to maintain productivity and ensure projects are completed. He also anticipates that companies that use ML technology will put more systems in place to monitor and govern performance, as well as make more data-driven decisions about how to manage ML or other technologies.



He also anticipates that companies that use ML technology will implement more systems to monitor and govern performance, as well as make more data-driven decisions about how to manage ML or data science teams.

 

“With clearly defined goals, these technical teams will have to be more key performance indicators-centric, so leadership can have a more in-depth understanding of machine learning’s ROI. “The days of ambiguous ML benchmarks are over,” Guttmann said.