We hear from a variety of technology professionals about their predictions for 2024, ranging from additional advancements in AI to cybersecurity and quantum computing.
A strong convergence of disruptive factors will transform the commercial landscape of 2024 as the year draws to a close. The creative potential and problem-solving skills of generative AI will reveal untapped efficiency. Sustainability will become a strategic requirement rather than just a slogan, especially when it comes to developing AI models. Furthermore, the once-science fantasy concept of quantum computing will unleash hitherto unthinkable possibilities.
Leading IT company executives are interviewed by Technology Magazine to learn more about the key themes to watch in 2024.
01: AI to take centre stage, moving from theory to practice
According to John Roese, Global Chief Technology Officer at Dell Technologies, the conversation around GenAI will transition from theory to reality, with changes in the cost and infrastructure of training to inference and operation costs.
Although there are many brilliant ideas about how GenAI can change business and society, there aren’t many large-scale, practical GenAI initiatives. The first wave of GenAI enterprise initiatives will mature by 2024, revealing significant aspects of the technology that were not previously known in its early stages, the speaker predicted.
02: A convergence of IT and security teams
Zeki Turedi, CTO Europe at CrowdStrike, believes that there will be a chance to improve organizational resilience by merging IT and security teams within businesses as new threats surface in 2024, blurring the barriers between IT and security roles.
Having previously worked in discrete units, these groups are witnessing a growing convergence of their goals and day-to-day activities. This change is brought about by the quick development of technology as well as the shifting nature of security threats that have an immediate effect on IT infrastructure.
This convergence is especially needed and timely because single attacks now target security and infrastructure at the same time, necessitating a coordinated response. Through increased cooperation and the sharing of tools and platforms, these hitherto dispersed teams can pool their knowledge to strengthen defenses against more complex cyberattacks. This tendency is demonstrated by the emergence of new cybersecurity solutions designed with IT teams in mind. By offering real-time information and automated reactions to security issues, these platforms are made to seamlessly interact with IT processes, speeding up response times and improving overall security posture.
03: Hyperscalers will drive a powerful, real-time ecosystem
Generative AI has frequently come under fire for using historical data to produce outcomes that are vital to the aim. But according to Rodrigo Liang, CEO of SambaNova Systems, the partnership between hyperscalers and AI models will completely transform the data analytics market by matching real-time fine tuning with current data and resulting in major gains in speed, accuracy, and cost.
He predicts that real-time fine-tuning will become more prevalent. This will enable models to comprehend and adjust to changing data, advancing the use of AI in applications across all sectors of the economy. “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, banking, and more will be made possible by the combination of advanced chips and hyperscale data capabilities, creating a powerful ecosystem.”
04: A renewed focus on zero trust models
People use more devices, apps, and services than ever before in today’s hybrid work environment, many of which are hosted in the cloud on systems that are physically independent of corporate IT. This new environment calls for a zero-trust framework.
According to Chris Peake, CISO and SVP of Security at Smartsheet, organizations will be adding more layers to their models in the upcoming year.
According to him, some organizations might implement role-based security, which enables them to designate responsibilities for various user types and control access in accordance with those roles. By doing this, they will be able to safeguard private data while lowering obstacles to entry for those who are authorized. Additionally, organizations can add time-based access, which enables them to control user access to information according to the duration of the project they are working on.
Furthermore, generative AI holds great promise for enhancing data security and introducing an additional degree of defense. Intelligent systems must take on the task of monitoring the vast amount of data that flows through a business because no one can do it manually. With continued development, machine learning will be able to “understand” normalcy and identify anomalies.
05: IT spend will be focused on business outcomes more than ever
Linda Yao, Chief Operating Officer and Head of Strategy, Lenovo Solutions & Services Group, forecasts that businesses will be focusing on getting more value from their IT spending in a few areas due to a developing macroeconomic and competitive landscape.
According to her, “the first is that they will demand more operational flexibility, whereby their investments scale in proportion to the value they return.” “Whether that means utilizing technology to stabilize revenue growth or to achieve cost savings, or implementing that technology in a way that allows for predictable cash flow payments, they will want more predictability in their cash flows.”
Additionally, companies will make sure that IT deployment either directly supports or promotes business results. More businesses will utilize IT in accordance with their desired business objectives, be they top line, bottom line, or to meet particular customer experience, sustainability, throughput, customer acquisition, or other metrics. Rather than implementing and maintaining technology in a vacuum, more companies will link their adoption of this technology to these KPIs.
when a result, when clients modernize or completely redesign their IT stacks, IT expenditure on old infrastructure will switch to investment on next-generation technology and increase quickly during the next five to ten years. This entails switching to hybrid cloud from legacy IT systems, embracing more virtualized and networked IT environments, and forgoing traditional software licensing in favor of highly customized tech on demand.
06: Quantum progress but not quantum leaps
Even before post-quantum cryptography (PQC) is standardized, Liz Centoni, Executive Vice President, Chief Strategy Officer & GM, Applications at Cisco, predicts that in 2024, PQC will be widely used as a software-based defense against quantum attacks on data, even in conjunction with traditional systems.
Browsers, operating systems, and libraries will all use PQC, and creative people will try incorporating it into protocols like SSL/TLS 1.3, which regulates traditional cryptography. PQC will begin to affect businesses as well, since their goal is to guarantee data security in the post-quantum era.
The increasing significance of quantum networking is another trend. In four or five years, or possibly longer, it will allow quantum computers to interact and work together to create more scalable quantum solutions. Information will be sent using quantum phenomena like superposition and entanglement in quantum networking. Quantum networking will also be used by QKD as a substitute or enhancement of PQC, depending on the desired level of security and performance. Government and financial industries, which have strict requirements for data processing and security, will spend heavily in quantum networking research.
07: Human skills will be essential for the uptake of AI
According to NTT’s 2023 Global CX Report, CEOs concur that human participation is still necessary for the bulk of CX contacts and that this will continue to be an essential component of customer journeys. Sashen Naidu, Vice President, CX Services at NTT Ltd., notes that while four out of five organizations intend to integrate AI into CX delivery during the next 12 months, the success of this initiative will depend heavily on the human aspect.
Businesses will focus more on filling the growing skills gap that will undermine AI ambitions as they consider how automation may supplement and improve human capabilities. Although most positions in many industries will require basic knowledge of AI and big data analytics, hiring new employees won’t be the sole option.
According to NTT DATA research, company executives are more likely to have witnessed profitability of more than 25% over the previous three years as a result of their investments in upskilling and reskilling programs. More carefully chosen educational opportunities will be offered in 2024 to assist address skills gaps and satisfy employer demands.
08: Continued rise of social engineering attacks
Identity-based attacks will remain the primary weapon used by threat actors in 2024, according to Turedi of Crowdstrike, for the straightforward reason that it is still a very effective tactic.
According to CrowdStrike’s most recent Threat Hunting Report, compromised identities are the cause of 80% of breaches. Adversaries are not only depending on legitimate credentials that have been compromised; instead, they are abusing all available means of identity and authorization, including weak credentials obtained from the dark web, and they have improved their social engineering and phishing techniques.
The salient feature here is social engineering, as companies work to teach their staff how to spot deception in common ways. Because of this, identity protection will be the most important safeguard that businesses should focus on enhancing in 2024. If not, enemies will consistently try to exploit this vulnerability, and they almost always succeed.
09: AI advancements will drive even more energy usage
In order to combat climate change, renewable energy is essential, as Cisco’s Centoni explains. Companies will start to save money on energy consumption as compared to generic systems by choosing smaller AI models with fewer layers and filters tailored to use cases.
These specialized systems effectively complete particular tasks after being trained on smaller, extremely accurate data sets. Deep learning models, on the other hand, make extensive use of data.
Energy efficiency will also be aided by the rapidly developing field of energy networking, which combines the capabilities of software-defined networking with a system of electric power comprised of micro grids that are connected by direct current. Energy networking, which applies networking to power and connects it with data, provides extensive visibility and benchmarking of current emissions as well as a point of access for optimizing power distribution, transmission, storage, and utilization. Energy networking will also assist businesses in more precisely measuring their energy use and emissions, automating various IT, smart building, and Internet of Things sensor operations, and freeing up wasted and inefficient energy. The network will function as a control plane for measuring, monitoring, and controlling usage thanks to its inbuilt energy management capabilities.
10: Businesses will focus on creating guardrails to mitigate AI risks
SVP and Chief Information Officer of Lenovo, Art Hu, predicts that organizations implementing AI will become more aware of the risks and underlying nature of the technology and that more will take focused steps to reduce this.
He states, “For instance, new patterns like retrieval augmented generation can help LLMs generate results from reliable sources.” The augmented intelligence that generative AI offers can be balanced by using additional strategies like guaranteeing the integrity and quality of training data and involving a human in both training (reinforcement learning based on human feedback) and inference for the most delicate scenarios.
Strong governance guidelines, procedures, and instruments will also be expanded upon, and testing and validation of AI-generated material as well as system-wide monitoring will be incorporated. The use of AI will be governed by a well-defined AI policy that specifies the standards for what constitutes morality, responsibility, and inclusivity. This, together with training to enable teams operating in this area to acquire the know-how required to put the guidelines into practice, will serve as the cornerstone around which companies implementing concrete AI strategies will build.
