6 trends defining the enterprise IT market today – CIO

When Rebecca Fox, group CIO at security consulting firm NCC Group, looks at today’s enterprise IT market, she sees a future shaped by multiple trends, but mostly by AI.
“Everyone is talking about AI,” she says, noting that most enterprises already have AI in their business. “It’s built into, or is being built, into existing SaaS platforms from the biggest providers.”
Yet accompanying AI’s arrival is a certain amount of fear and trepidation, Fox says. Questions abound. “What would a fully enabled-AI business look like? Would it have the same workforce, in the same locations?” These aren’t questions that need answering today, but they do need considering, she says.
This and several other emerging trends may be poised to reshape both IT and business in the years to come. And that is why Saket Srivastava, CIO at workflow technology management company Asana, believes there has never been a better time to be a CIO.
“While there are uncertainties around AI and the future of work, it’s an exciting era for IT leaders to use new technology to drive strategy, help decision making, and inform planning,” he says.
To help you keep pace with relentless change, here’s a look at the top trends impacting today’s enterprise IT market.
Generative AI stands alone as today’s most important IT market trend. “We often see trends that affect a few parts of an organization, but generative AI has the potential to be a catalyst for change from back office to consumer products and everything in between,” says Mike Storiale, vice president of innovation development at financial services firm Synchrony.
Catalyst technologies like generative AI create a demand for change, Storiale says. “The demand is exciting and unlocks massive potential, but also creates a need for IT organizations to be laser-focused in how they prioritize and scale the tools needed to empower the organization, while also being responsible.”
It’s critical, he adds, to embrace the paradox: “You will need to move fast and be prudent at the same time.”
Gen AI is driving creativity, enhancing everything from employee experience to development operations to customer experience, Storiale says. At the same time, there’s an increased focus on what needs to be prioritized to ensure that enterprises have the resources and tools in place to meet gen AI’s demands.
“Much like other catalyst trends, we’ll see an explosion of ideas in the short term, followed by groundbreaking transformation, and then a settling into the use cases that work,” he predicts. “Over time, we expect that gen AI becomes as baked into operations as other catalysts before it, like the internet, mobility, and the cloud.”
Generative AI will enable enterprises to use data with great efficiency and productivity, says Lori Beer, global CIO at JPMorgan Chase.
“It’s early in the gen AI journey, but this is transformational,” she observes. Teams across industries are evaluating how their organizations can use data more effectively. “For a company like JPMorgan Chase, we have an incredible amount of data, and data fuels AI, allowing us to highly differentiate our capabilities, services, and products to our clients, customers, communities, and employees.”
Beer believes that for her enterprise, generative AI will lead to higher levels of personalization, more targeted messaging, tailored stock recommendations, efficiently summarized earnings reports, and streamlined internal processes.
While current quantum computers are primarily advanced research machines, they may soon affect every aspect of the business world, just as generative AI has disrupted enterprises, predicts Scott Buchholz, managing director at enterprise advisory firm Deloitte Consulting.
“While IT leaders are still trying to make sense of how and when it will affect their businesses, quantum computing has incredible potential to disrupt industries like energy, finance, cybersecurity, and more,” he says.
Quantum computing technology is well suited for dealing with optimization, machine learning, and data analytics. “It’s likely to be useful for businesses across a spectrum of activities, from supply chain optimization and vehicle routing to predictive modeling to complex derivative valuation,” Buchholz says. Quantum computers are also likely to transform adopters’ understanding of, and ability to simulate, both chemistry and materials science. “We may soon reach the point at which quantum computers can solve problems that cannot be solved by today’s supercomputers.”
For over a decade, IT leaders have invested in various “silver bullets” they hoped would solve all of their pressing problems, says Christian Kelly, managing director at enterprise consulting firm Accenture. “Each time, most IT organizations adopted the new technologies and models at a micro-level, without changing their technology architecture — the way they work or the way they engage with their upstream and downstream business partners.”
Such past experiences have led many CIOs to reconsider their existing cloud investments and to slow down their cloud migrations. “These leaders have reported that the cloud has resulted in them spending more money than they anticipated without seeing the promised ROI,” Kelly says. “This is occurring because these CIOs didn’t make the structural changes needed to unlock the full potential of the technologies they pursued.”
IT security is continuing to move toward a zero-trust security model, based on the idea that anything inside or outside an enterprise’s networks should never be implicitly trusted.  
“While zero-trust isn’t a cybersecurity solution in and of itself, implementing a zero-trust architecture should help mitigate and ultimately lower the number of successful cybersecurity attacks on an organization,” says Robert Pingel, operational technology security strategist at industrial automation firm Rockwell Automation.
Maintaining a vigilant zero-trust architecture requires constant adaptation. “The first line of defense lies in regular vulnerability assessments and testing to identify weaknesses and prompt continuous improvement,” Pingel says. Incorporating updated threat intelligence and adapting policies and controls is also important to stay on top of evolving cyber threats.
Multiple vendors are addressing the rapidly growing zero-trust trend. Monitoring and logging technologies play a crucial role, providing real-time visibility into user activity and suspicious behavior. “This allows for prompt investigation and remediation, preventing breaches from escalating,” Pingel says. “Automation streamlines repetitive tasks like access control updates, and anomaly detection, freeing security teams for strategic tasks.” Regular employee training can also foster a culture of security awareness, empowering everyone to identify and report potential threats.
A growing number of CIOs are doubling down on cyber resilience, says Ron Culler, vice president for cyber development programs at the Computing Technology Industry Association (CompTIA). He observes that cyber resilience is focused on keeping an enterprise operational when an attack happens. “Simply, it’s about keeping your company alive.”
Cyber attacks are inevitable, but disasters and accidents can also damage or destroy digital assets and data. “A cyber resilience strategy builds the plan for how you deal with these issues when they occur,” Culler says. As with zero-trust security, numerous vendors are working to supply customers with cyber resilient-oriented tools and services.
Achieving cyber resilience starts with identifying risks. “You need to know what you need to protect and why,” Culler says. “This isn’t just about your IT systems, it includes the business units they support and, ultimately, the company as a whole.”
Culler adds that cyber resilience isn’t the sole responsibility of IT and security leaders. “It requires buy-in and active participation from everyone, from the board to the employee,” he explains. “Once you’ve identified your risks, create your policies and plans, test them, learn from the mistakes, and start again.”
NCC Group’s Fox warns that AI is emerging as a huge data access challenge. “When using AI at the enterprise level, how and where your data is stored, and who has access to it, is crucial,” she says.
Fox notes that some technology providers have already created AI environments that restrict data to their host organizations. But she wonders whether, as datasets grow, organizations will be able to manage permissions on who can access what data. By its very nature, AI is weakly structured, which makes controlling data a challenge.
“Deleting data from an AI model is not like deleting an email or record from a database; it’s far more complex,” Fox says. “It will require new specialist skills to manage AI data models.”
John Edwards is a veteran business technology journalist. His work has appeared in The New York Times, The Washington Post, and numerous business and technology publications.


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