As the year comes to an end, the business landscape of 2024 will be reshaped by a potent confluence of disruptive forces. Generative AI’s creative might and problem-solving prowess will unlock hidden efficiencies. Sustainability, no longer a buzzword, will morph into a strategic imperative, particularly when it comes to building AI models. And quantum computing, once science fiction, will crack open once-unimaginable possibilities.
1: AI to take centre stage, moving from theory to practice
John Roese, Global Chief Technology https://ryuukoi.id/ Officer of Dell Technologies expects that the GenAI dialogue will move from theory to practice with shifts from training infrastructure and cost to inference and cost of operation.
“While GenAI has sparked incredibly creative ideas of how it will transform business and the world, there are very few real-world, scaled GenAI activities. As we move into 2024, we will see the first wave of GenAI enterprise projects reach levels of maturity that will expose important dimensions of GenAI not yet understood in the early phases,” he said.
2: A convergence of IT and security teams
As new threats emerge in 2024, blurring the lines between IT and security responsibilities, Zeki Turedi, CTO Europe at CrowdStrike, predicts that there will be an opportunity to enhance organisational resilience by converging IT and security teams within enterprises.
“Traditionally operating in separate silos, these teams are finding their objectives and daily operations increasingly intertwined. This shift is driven not only by the rapid advancement of technology but also by the evolving landscape of security risks that directly impact IT infrastructure.
3: Hyperscalers will drive a powerful, real-time ecosystem
Generative AI has often been criticised for tapping into old data to drive mission-critical results. However, SambaNova Systems’ CEO, Rodrigo Liang, predicts that the collaboration between hyperscalers and AI models will revolutionise the entire data analytics landscape, matching current data with real-time fine tuning, leading to significant speed, accuracy and price improvements.
“We’ll continue to see a shift towards real-time fine-tuning, allowing models to adapt and understand current data, thus driving advancements in AI applications in every industry,” he says. “The combination of advanced chips and hyperscale data capabilities will create a powerful ecosystem, enabling the development of very large Composition of Experts models to address even more complex use cases than what we’ve even come close to seeing today in industries like marketing, advertising, healthcare, climate, banking and more.”
4: A renewed focus on zero trust models
In today’s hybrid work environment, people rely on more devices, apps, and services than ever, many of them hosted in the cloud on systems that are physically outside the control of corporate IT. This new landscape requires a zero-trust model.
In the coming year, Chris Peake, CISO and SVP of Security at Smartsheet, predicts that we’ll see organisations add extra layers to their models.
“For example, some organisations might add role-based security, allowing them to define roles for different types of users and manage their access accordingly,” he says. “This will enable them to protect sensitive information while reducing the barriers to access for authorised individuals. Organisations may also add time-based access, allowing them to manage users’ access to information based on the length of the project they’re working on.
5: IT spend will be focused on business outcomes more than ever
Faced with an evolving macro-economic and competitive landscape, Linda Yao, Chief Operating Officer and Head of Strategy, Lenovo Solutions & Services Group, predicts that businesses will be focused on deriving more value from their IT spending in a couple of ways.
“The first is they will demand more flexibility in their operations, in terms of having their investments scale with the value they return,” she says. “They will want more predictability in their cash flows, whether that means using technology to stabilise revenue growth or to achieve expense savings, or implementing that technology in a way that allows for predictable cash flow payments.