With the pace of technology quickening, 2024 is shaping up to deliver another round of breakthroughs that promise to fundamentally reshape how the world lives, interacts, and communicates.
Pushing the boundaries of innovation, artificial intelligence (AI) and machine learning (ML) are poised to begin making serious impacts by enabling other technologies such as 6G, cloud computing, networking, and electronic design automation (EDA). With cybercrime posting the world’s third largest GDP, cybersecurity will continue to be an important topic, seeing the harmonization of IoT security standards, a focus on AI, and improvements in the global supply chain.
In wireless communications, full 5G capabilities will come to fruition, while progress will be made in defining 6G technologies and standards. The upcoming year will also see a host of semiconductor innovations including chiplets, new standards, and a continued focus on software-based test and design. In addition, quantum computing will begin to move from theory to reality with the emergence of quantum-as-a-service.
Looking ahead, Keysight Technologies executives share insights on the innovations, trends, and tech topics that will shape 2024.
Gareth Smith, General Manager, Software Test Automation
AI and testing—Always on becomes the baseline: As AI becomes increasingly embedded in software, the systems will become more autonomous, which increases risk and complexity and makes testing a real challenge. As a result, a fixed set of tests (scripts) will no longer suffice when evaluating intelligent systems. Instead, AI will be needed to automatically and continuously test AI applications. The future of software testing is autonomous test design and execution.
Why AI may drive quality down, not up: As AI permeates every system and complexity and sophistication soar, there’s a risk that quality will go down. This is a result of the sheer number of permutations, which makes testing everything impossible. Thus, decisions will need to be made around how, what, and when to test to ensure quality is maintained.
AI regulation needs to be deep and wide: There’s universal acceptance of the need to regulate AI. However, what the regulation should encompass will be subject to much debate due to the breadth and complexity of the technology involved. It will take a seismic event with significant negative consequences before the necessary funding is available. Only then will clear standards and best practices come into effect. If regulation doesn't happen in the near future, it increases the risk that AI will no longer be able to be reined in.
Why AI needs a driver’s license and a regular inspection: Currently, AI systems are tested by the companies building them. As the risks are increasingly understood, having an independent body to verify that an AI system is compliant is essential. Gaining an AI certification (i.e., AI driver's license) will be the first step.
However, just like your car, it will require a regular test to ensure it remains ethical, responsible, free of bias, and meets the necessary country and industry standards. In the longer term, this may result in an NFT label on each AI system to validate that it’s fit for purpose and meets all of the required criteria.
Goodbye citizen developer, hello business developer: Citizen developers have long been touted as the answer to the IT talent shortage. However, the rapid growth of AI-powered solutions is fueling a new generation of business developers. These domain experts will increasingly be involved in the software-development lifecycle (SDLC) as they understand the goals and operations of the enterprise.
This will give rise to a new wave of no-code systems that enable business users to define goals and then have AI technology close the gap. The operational knowledge ensures that the software meets the specific needs of the organization and mitigates the risk.
Dan Thomasson, Head of Central Technology and Vice President of Keysight Labs
6G embraces AI for network optimization: 6G will turn to AI for network optimization, which will create testing challenges. It will be vital to develop technologies that can test AI algorithms to ensure training data is free of bias and the models are effective and devoid of anomalous behavior.
Bridging the simulation gap with AI: Moving forward, AI technologies will underpin simulation models, ushering in a new era of more accurate, capable, and informative models. In addition, the intelligence will provide enhanced insights into measurement data, reduce errors, and help optimize the design and test workflow.
Roger Nichols, 6G Program Manager
Why some versions of AI are not the key to optimizing 6G networks: AI has a large role to play in helping optimize 6G. However, it will not be the much-hyped generative AI that relies on large language models (LLMs) and vast data sets. Instead, it will be domain-specific data combined with the power of AI models and wireless domain expertise that will help solve specific industry problems.
For example, AI algorithms will make improvements in the air interface, helping optimize the 6G system. Other use cases include advancing how to manage mobility during handovers, cell-site planning, and optimizing MIMO. But, before AI can add value to the development of 6G, it needs to be more reliable, explainable, and much less expensive.
Skills silo throttles integration of AI in 6G: Domain knowledge and AI expertise are vital to successfully integrating AI into 6G networks. Today, we have either wireless experts or AI specialists, but too few heads that share expertise in both domains. Until these skill sets are blended, it will be tough to find the right resources to deploy AI effectively in support of 6G goals. I believe this workforce capability gap will take more than a decade to resolve.
Sarah LaSelva, Director of 6G Marketing
AI is everyone's BFF, including 6G: The combination of complexity and massive amounts of data makes wireless networks ripe for AI optimization. The technology has started to be integrated, and in 2024 this will accelerate. A key part of the process will be understanding where AI can help and, crucially, where it's not the answer and may hinder the rollout of 6G.
AI + 6G: A measured approach: Unlike other sectors, the wireless industry will take a more measured approach to integrating AI. Operators will focus on thoroughly training the machine-learning models on diverse datasets, quantifying the impact, and putting a new test methodology in place. As AI adoption matures, it will transform the wireless industry over the next decade, unleashing new capabilities such as improved beam management and smart spectrum sharing.
Dan Krantz, Chief Information Officer
Impact of AI in the cloud-computing market: AI workloads require GPU and memory-intensive capacity. In the past, we thought of cloud computing as having three primary competitors: AWS, Azure, and GCP. Generation 2 of the Oracle Cloud Infrastructure (OCI), with its significant price and performance advantage in GenAI training, has created a 4-horse race in the cloud-computing space now.
Niels Faché, Vice President & General Manager, Design and Simulation
EDA turns to AI—From complexity to clarity: The application of AI and ML techniques in EDA is still in the early adopter phase, with design engineers exploring use cases to simplify complex problems. The intelligence is particularly valuable in model development and validation for simulation, where it assists in processing large volumes of data.
In 2024, organizations will increasingly adopt both technologies for device modeling of silicon and III-V semiconductor process technologies, as well as system modeling for forthcoming standards such as 6G, where research is well underway.
Marie Hattar, Senior Vice President & Chief Marketing Officer
Copyright comes into focus: Generative design tools are increasingly being adopted, but one thorny issue is copyright. Many of these AI solutions scrape visual content without being subject to any consequences.
In 2024, there will be a lot of energy and effort focused on finding a solution to the copyright problem with AI image creation to clarify ownership. This will enable marketing teams to embrace AI design tools without fear of encountering legal issues, saving precious time and money.
Customer engagement—AI in the driving seat: By the end of 2024, most customer emails will be AI-generated. Brands will increasingly use generative AI engines to produce first drafts of copy for humans to review and approve. However, marketing teams must train LLMs to fully automate customer content and differentiate their brand. By 2026, this will be commonplace, enabling teams to shift focus to campaign management and optimization.
AI and talent—The augmentation era: As AI becomes more pervasive, this will inevitably change the fabric of marketing teams. Lower-level admin-centric roles will disappear, and many analytical positions will become redundant.
However, it's not all doom and gloom. The demand for data scientists will explode, making it one of the most sought-after skill sets for the rest of this decade and immune to economic pressures. Humans will continue to drive marketing, but the role of machines will increase each year. This era of AI (with guardrails) augmenting humans will continue for at least another decade in marketing.
AI and retail: The retail industry has been quick to integrate AI to deliver efficiencies and increase sales. One innovation on the horizon is combining neural networks with a shopper and a product to create a new retail experience.
For example, starting in 2024, you can expect an AI assistant to showcase an item of clothing on a model with similar dimensions to you so you can see exactly how it will look in various poses. These immersive, highly personalized experiences are the future of retail.
AI and digital twins changing the face of healthcare: Digital twins are increasingly ubiquitous, and now, with AI-infused, they’re creating a new reality in healthcare. The technology will significantly reduce the pressure on the system and provide individuals with more options, helping improve the quality of life.
AI-powered digital twins will usher in a new era of caring for an aging population, allowing people to live independently for longer. AI will play a pivotal role in the early diagnosis of potential health issues.
For example, full-body MRIs will tap into AI's ability to identify, predict, and analyze data patterns to help diagnose disease long before it's visible to the human eye. In addition, AI will take on a more prominent role in assisting medical staff to understand and interpret findings and provide treatment and care recommendations.
Scott Register, Vice President, Security Solutions
Cybersecurity in the AI era—The good and bad: AI is making an impact on every aspect of our lives, including cybersecurity. Adversarial AI will increasingly be a problem.
For example, generative AI can collect information from social media, corporate email, blogs, and other sources to generate specific and realistic phishing emails that can be personalized and mass-produced with almost no human input. As a result, companies must deploy more advanced phishing detection systems, including those optimized to detect AI-generated content and improve employee training.
AI will increasingly be used to generate network or endpoint behavioral patterns to see if different security products can identify them. Because a lot of detection occurs at the security information and event management (SIEM), this can be tested via log messages rather than actual behavior. Thus, AI is perfectly suited to take on this task. AI will increasingly take on a pivotal role in testing and evaluating security products.
Data privacy remains in the spotlight: Data privacy is a critical component of cybersecurity, and how you think about it differs significantly from areas like intellectual property. Stringent enforcement of who and what has access to personal identifiable information (PII) data, and how to manage it securely, requires special attention and specific skills. Increasingly, organizations will outsource the management of PII to help step up their efforts to protect the data and shift more of the risk to a third party.
Supply-chain diversification is crucial to resiliency: Organizations will start to push more risk assumption into the supply chain to protect themselves against inherited security flaws. In 2024, there will be stricter documentation requirements for secure design, implementation, and validation of supply-chain components. To build resiliency, organizations will diversify their supply chain for critical parts.
Critical infrastructure in the crosshairs of threat actors: Critical infrastructure is a main target of cybercriminals. If the wars in Ukraine or Israel spread, this will drive up the number of attacks from threat actors loosely aligned with nation-states. We’ve already seen increased attacks on utilities, and in 2024, this will expand to include connected medical and smart-home devices.
Cybersecurity—People and policies trump products: Products are an essential part of cybersecurity. However, people and policies are critical to fine-tune and strengthen defenses. For example, testing your security stack and up-skilling your team will bolster your cybersecurity posture more than adding another dashboard.
International harmonization of IoT cyber regulations: There are numerous country-wide regulations to improve IoT cybersecurity, including the Cyber Trust Mark in the U.S., the ETSI EN 303 645 standard in Europe, and a labeling program in Singapore. In 2024, there will be more harmonization of the legislation to avoid manufacturers having to grapple with a multitude of requirements, which slows production and drives up costs. However, a global standard will remain elusive for now.
Intelligent security testing is non-negotiable: Cybercrime is the world’s third largest GDP, and organizations are under constant attack. Bad actors are already using intelligent tools to try to access networks, so it's vital for enterprises to strengthen their defenses by integrating AI-driven security testing. Companies that fail to embrace intelligent testing are leaving flaw discovery within their network to bad actors. As always, you want to find it before they do!
Gareth Smith, General Manager, Software Test Automation at Keysight
Cybersecurity and AI—Constant vigilance the new norm: As the risks associated with AI are recognized, enterprises will need to appoint an AI and security compliance officer to the C-Suite. Over time, this role will merge with the CSO.
With live learning, it will be vital to have guardrails in place to keep AI on track. Constant checks and balances will be essential to validate that an intelligent system is behaving and hasn't gone rogue. Live surveillance will become standard.
However, as these systems develop, it will also be necessary to test that they haven't learned how to look like they’re behaving while undertaking nefarious activity. Reinforcement learning and similar techniques can inadvertently drive the AI to cover its tracks to reach its goal and will be a huge challenge to address before the end of the decade. These problems will create a slew of new opportunities for companies that can help clean up, control, and put guardrails in place for AI.
Hwee Yng Yeo, Automotive Solutions Lead
Connected cars in the crosshairs of cybercriminals: As vehicles continue to have more systems and technology embedded, it increases the attack surface for cybercriminals to exploit. Advancing cyber-hacking tools are challenging security teams to mitigate threats beyond direct attacks against vehicles, targeting fleets, mobility applications, and services, and even EV charging infrastructure.
In 2024, the auto industry ecosystem will continue investing to enhance and increase cybersecurity throughout the vehicle's lifecycle, from design to production and maintenance. This includes rigorous vehicle testing, from physical layers such as onboard in-vehicle networks, communications, and EV charging ports to securing application-layer protocols.
Roger Nichols, 6G Program Manager
5G still a work in progress: At the end of 2023, there were fewer than 50 commercial standalone 5G networks in the world. Over the next few years, the pace of transition from non-standalone to standalone networks will accelerate as these architectures support a fully programmable 5G network, which in turn enables operators to build services beyond enhanced mobile broadband.
The expansion of standalone networks should pick up, as will the use of network slicing and resolving defects and performance challenges. In addition, the 5G ecosystem will grow to support capabilities in a broader range of industries beyond gaming and social-media activities. This will lay the groundwork for 6G to be used across a wide set of use cases.
Mobile gaming turns FR2 from dormant to dominant: The wireless industry is exploring the acquisition of new spectrum between 7 and 24 GHz. However, FR2 (millimeter-wave, 24 to 52 GHz) is already available with many cases allocated, but it's too expensive to support current use cases. FR2 will require new mobile gaming/VR applications to drive the economy of scale to overcome this hurdle.
Interest from Gen Z and Gen Alpha in the new consumer applications played on VR/AR devices rather than traditional smartphones will drive a surge in the demand for higher bandwidth and capacity with a low-stakes use model. Current networks will be unable to support this, and operators will turn to FR2 to support the demand at this scale. Once this milestone occurs, the downward pressure on costs will help applications outside the entertainment and advertising realm use FR2.
Mobile sub-THz radio systems will not come to fruition anytime soon: Mobile sub-terahertz (sub-THz) radio systems are at least a decade away. They’re not feasible from a mobility standpoint due to immature mobile technology and the associated costs—not to mention power consumption and data management. The industry’s struggles with FR2 are evidence that mobile sub-THz radio systems will not be viable in the near future.
6G is not going to overhaul the core network: 6G will not result in a major overhaul of the core network. It will evolve, but a significant revamp, as happened with network functions in the transition from 4G to 5G, will not occur. The majority of the wireless industry now accepts that this would be a mistake.
Spectrum smorgasbord—A huge challenge for wireless industry: Over the next five years, the global wireless industry will have to support and manage 2G, 4G, 5G, and 6G networks. This carries significant technical and business challenges. With more than a fifth of the world's population still relying on 2G, developing regions like Africa and most of Asia will not sunset many legacy networks before the end of the decade.
However, India is bucking this trend and deployed country-wide coverage with 5G standalone networks, making it the largest country in the best position to retire 2G. The only constraint that could slow this shift is the affordability of new devices.
India—From wireless laggard to 6G leader: India has become a nation of data guzzlers and is the global leader in per-device monthly data consumption. This is driving the demand for more bandwidth and capacity. After being late to adopt 4G, but accelerating 5G in the past 12 months, the country is emphasizing and championing national objectives for 6G and looks to help shape and drive its rollout.
India has launched multiple 6G research initiatives in 2023. They will be a leading voice in establishing 6G standards and ensuring it’s fit for purpose for countries with large rural populations.
Metaverse—More than an entertainment destination: Despite most discussions of the metaverse focusing on gaming, it will evolve to support much broader use cases than those laid out by Meta. By the end of the decade, augmented and virtual reality will be part of our daily lives, and 6G will be pivotal in providing the bandwidth and connectivity to support these synthetic environments and facilitate seamless interactions between the virtual and physical worlds.
Sarah LaSelva, Director of 6G Marketing
Regulation on the radar: In 2024, regulation will be on the agenda. The industry will attempt to provide a framework so that the entire ecosystem, including companies, operators, and countries, can work in unison. Due to the complexity involved, particularly at the geopolitical level, this will take several years to resolve.
Spectrum-sharing logjam on the horizon: 6G will leverage many different bands and tools to meet the growing demands and expectations for cellular communications. The most challenging technical aspect is how to share spectrum.
For example, in 6G, the upper mid-band (7 to 24 GHz) is already used by civilians and governments for meteorology, radio astronomy, and maritime radio navigation. Once wireless access is added, it will necessitate learning how to be good frequency citizens. In 2024, a lot of research will focus on this area to find a pathway forward.
Global spectrum harmonization on the radar for 6G: The World Radio Conference in late 2023 will determine the available frequency bands that 6G will use and put in place a plan to make global spectrum harmonization a reality. This will enable operators to realize economy of scale for components and limit the number of bands to support.
Jeff Harris, Vice President, Corporate and Portfolio Marketing
The next frontier in EVs—Prioritizing and predicting battery health: As electric vehicles evolve, range anxiety will start to dissipate as 300 miles becomes standard. However, attention will shift to the health of batteries. With cell phones already illustrating how batteries can deteriorate over time, no driver wants to experience a car that quickly loses power, potentially leaving them stranded or, at the very least, requiring multiple charges per day.
Battery health will become a factor influencing EV buying decisions, presenting an opportunity for auto manufacturers to visualize a car's health status to reassure and inform drivers. The information will be more granular and incorporate gamification interfaces so that drivers can see the influence of their actions, keeping the battery-management system at peak performance. In addition, by integrating AI algorithms into the system, it will predict the health and performance of batteries under various conditions, quelling any concerns.
Hwee Yng Yeo, Automotive Solutions Lead
Cars run the world—Vehicle-to-grid implementation: One of the most significant areas of investment by the public and private sectors is in distributed-energy resources. In October 2023, the U.S. Department of Energy announced that $3.5 billion will go toward expanding wind and solar power capacity, harden power lines against extreme weather, integrate batteries and EVs, and build out microgrids to keep the lights on during power outages. This is part of the $10.5 billion available to expand transmission lines, improve grid resiliency, and deploy “smart-grid” technologies.
EVs will start to become vehicle-to-grid (V2G)-enabled, which turns the vehicle into a battery pack capable of bidirectional power flow that’s able to discharge stored electricity back to the grid. However, connecting V2G-enabled EVs to the grid is extremely complex. Moreover, distributed-energy resource manufacturers for EVs must comply with multiple standards and certification processes before they can go to market as V2G-compliant.
Solid-state EV batteries shift from concept to reality: It took solid-state drives almost 30 years to become pervasive. However, despite work on solid-state batteries for electric vehicles getting underway just over a decade ago, they’re now in the final stages of fine-tuning, offering automakers an array of benefits that include:
- Lighter: A compact and more lightweight battery increases the driving range.
- More stable: Unlike lithium-ion batteries, which use liquid electrolytes, solid-state batteries use solid electrolytes, typically made of ceramics or polymers. These are more stable and secure, generating much less heat than their liquid counterpart.
- Faster, more durable: Solid-state batteries can reach 80% charge in 15 minutes and maintain 90% of their capacity after 5,000 charges, unlike lithium-ion, which begins to degrade after 1,000 cycles.
Asia Pacific leads the charge: In 2024, research in solid-state batteries will intensify, with market growth led by Asia Pacific followed by Europe and the U.S. For example, South Korea announced a $15 billion investment to commercialize solid-state batteries by 2030. And China's Guangzhou Automobile Group is pushing an even more aggressive timeline, stating it will roll out all-solid-state batteries in vehicles by 2026.
Closing the gap toward fully autonomous driving: In November 2023, BMW joined Mercedes-Benz to offer SAE Level 3 conditionally autonomous driving. Drivers can legally take their hands off the steering wheel “in certain conditions,” but are expected to resume control when prompted.
In 2024, automakers will continue refining Level 3 self-driving capabilities to make them increasingly available in consumer vehicles. Concurrently, commercializing Level 4 self-driving will continue.
However, to minimize the risks and liabilities of self-driving features, numerous iterations of design validation and testing must be done for the sensors and algorithms that take over from the human driver. One of the biggest challenges is training the algorithms to handle real-world traffic scenarios, from slow country roads to bustling peak-hour city traffic and one-in-a-million contingencies like a moose crossing the road.
Semiconductors / Electronic Design Automation
Advanced semiconductor innovations on the horizon: Connecting the digital and physical worlds will require more powerful digital processing and interfaces that can overcome increasingly complex signal physics. An array of advances in semiconductor technologies will be essential to achieve this goal and overcome the associated challenges. These issues include increasing data rates that need wider bandwidths, which dictate higher carrier frequencies, extending into the terahertz realm for wireless.
Utilizing techniques such as extreme MIMO adds more complexity and density. And networks with diverse topologies—e.g., using non-terrestrial (satellite) links—magnifies the challenge.
Innovations to address this will include combining commercial semiconductors, such as GPUs and FPGAs, with custom MMICs and ASICs. These new solutions will deliver significant improvements in size, weight, performance, and power consumption. Data converters enabling the capture and generation of signals at the widest bandwidths with unsurpassed signal fidelity will be needed, too. In addition, photonic solutions will be critical to extend the reach and capacity of data-transmission technologies.
Seamless software solutions for design and test: Currently, workflows are a set of loosely connected tools. However, as the virtual and physical worlds merge, a unified design and test workflow is required, one that shares data seamlessly via the cloud between simulation and measurement steps.
That information will be constantly analyzed to understand the behavior of simulation and measurement, eliminating any gaps in the workflow from concept to final test. The insights from the simulation will be fed into AI-driven tools that will elevate the speed and productivity of the design and test workflow. Digital twins will be used to tightly couple design and test so that only one actual build is needed.
Niels Faché, Vice President & General Manager, Design and Simulation
Predicting performance remains imperative in electronic design: In 2024, engineers will continue embracing shift-left with their electronic product development cycles. As design moves from the physical into the virtual space, engineers can more efficiently discover and fix problems, providing greater insights and performance improvements.
The next few years will see continued emphasis on connecting design and test workflows to handle rising complexity and more demanding time-to-market requirements for electronic products in wireless, wired, aerospace & defense, and other industries.
3DIC and heterogeneous chiplets—New standards come into view: New standards such as Universal Chiplet Interconnect Express (UCIe) are emerging for the creation of chiplets. They also involve the disaggregation of system-on-chip (SoC) designs into smaller pieces of intellectual property that can be assembled into 2.5D and 3D integrated circuits using advanced packaging. For designers to accurately simulate die-to-die physical-layer interconnect, it will require high-speed, high-frequency channel simulation to UCIe and other standards.
Software automation empowers engineers: As Moore’s Law reaches its limits, improving design processes through workflow automation will provide a pathway to increasing the productivity of design engineers. In 2024, software automation techniques, such as Python APIs, will take a more significant role in integrating “best-in-class” tools into open, interoperable design and test ecosystems.
Navigating the digital shift—Design management essentials: With the creation of digital enterprise workflows, many organizations are investing in design management across toolsets, data, and IP. Moving forward, design data and IP management software will play a critical role in the success of complex SoC and heterogeneous chiplet designs supporting large, geographically distributed teams.
The creation of digital threads between requirements definition and compliance, as well as establishing tighter links with enterprise systems such as PLM, will play a role in the digital transformation of product development cycles.
Silicon photonics fuels data-center transformation: Data centers are evolving to provide higher compute performance to support the exponential growth in AI and machine-learning (ML) workloads, as well as the need for more efficient power utilization and thermal management.
Silicon photonics will play a critical role in accelerating the transformation of data centers to meet the appetite for compute performance. As design engineers develop high-speed data-center chips that incorporate silicon-photonics interconnect, they will need process design kits (PDKs) and accurate simulation models that support the advanced development work.
Dr. Philip Krantz, Quantum Customer Success Manager
From theory to reality—The quantum potential: Quantum technology allows us to harness the fundamental laws of quantum mechanics to solve problems that are extremely challenging or impossible today. With quantum technology, complex simulations and computations, secure communication, and more powerful imaging and sensor techniques will be possible.
Navigating the quantum landscape—Bridging the talent gap: Quantum technologies are expanding beyond the academic realm and into startups, high-tech companies, and the military. This will give rise to more quantum hubs, incubators, and local and national ecosystems all trying to build a workforce that’s able to seize the quantum opportunity. Solving the talent gap is critical to realizing the potential of quantum in the coming years and decades.
From labs to lecture halls—The quantum leap in education: The shortage of quantum talent will create an opportunity for higher education to offer new programs to help train the future quantum workforce. By 2030, quantum courses will be commonplace.
These programs will involve industry partners so that students can access the latest quantum control and readout technologies and obtain the right technical skills. In addition, business schools will offer quantum courses to prepare the next generation of entrepreneurs to enter the quantum ecosystem.
Democratizing quantum—The emergence of quantum-as-a-service (QaaS): Due to the significant cost and resource burden in developing quantum labs, this will give rise to more quantum-as-a-service (QaaS) providers. Remote cloud access to quantum processors, test beds for device characterization, and foundries that offer fabrication services represent examples of services that are available, which in turn will help attract startups into the quantum ecosystem.
QaaS providers, over time, will help standardize device operation, characterization, and fabrication. This will lead to benchmarking of quantum processors and qubit-adjacent enabling technologies.
Inclusive innovation—Quantum community champions gender equality: Quantum has the potential to become the first technology sector to achieve gender equality. This will result from an ongoing concerted effort to attract women and ensure that a diverse workforce is the norm rather than the exception.
Knowledge gaps will throttle the progress of quantum: Quantum research and development will continue to attract investment from governments, academia, and industry. However, knowledge gaps and the availability of state-of-the-art technology will limit the pace of progress. For example, if the capability to produce high-quality quantum processor units (QPUs) is missing due to the lack of an advanced and dedicated cleanroom facility, this will slow progress.
Niels Faché, Vice President & General Manager, Design and Simulation
Next-gen quantum design—Optimizing system performance: Quantum computing is advancing at a rapid pace and transitioning from predominantly free research tools to commercial products and workflows in quantum design. Next-generation quantum design will require more integrated simulation workflows that provide developers with fast and accurate capabilities to optimize system performance.
Mark Pierpoint: Vice President of Strategic Innovation and Partnerships
Energy consumption drives technology decisions: Technology decisions, rather than solely evaluating performance and cost, will increasingly consider sustainability. Energy efficiency will be a C-suite imperative influencing every decision to achieve environmental goals.
Need for more energy alternatives: To support the shift to more renewable energy, the grid will increasingly need to add storage to enable utility companies to efficiently manage the peaks and troughs of demand. Furthermore, before the end of the decade, there needs to be a widespread acceptance that nuclear energy is a critical component required to meet net-zero goals.
Microgrids will play a bigger role: Today, we lose about 50% of electrical energy through losses in distribution, so microgrids will become increasingly popular as they can generate, distribute, and control energy close to where it’s used. The ability to provide reliable and resilient power will see them employed in a diverse range of applications spanning suburbs, rural electrification, military bases, and critical infrastructure facilities.
Gareth Smith, General Manager, Software Test Automation
AI and the sustainability quandary: There’s been significant hype around how AI systems will transform our lives, but little attention has been focused on the compute power that’s required. In 2024, AI's impact on sustainability will enter the spotlight, and organizations will start to monitor the carbon footprint of their entire technology infrastructure as they strive to meet net-zero targets.
As a result, companies will need to decide where and how to judiciously use AI rather than thinking it can be deployed everywhere. And when it comes to testing software and applications, businesses will also have to pivot from testing everything to predicting the tests that matter most to reduce the environmental impact.
Sarah LaSelva, Director of 6G Marketing
The wireless drive to net zero: With sustainability concerns growing around wireless networks, AI will play a pivotal role in helping reduce the environmental impact of 6G. For example, the technology can determine how to optimize power consumption by turning on and off components based on real-time operating conditions.
As 6G networks roll out and more devices and machines become wirelessly connected, it will create an opportunity to optimize operations and reduce carbon footprints. For example, 6G will help autonomous vehicles become more advanced, which will reduce traffic and some of the waste and inefficiencies associated with human-led driving. In farming, IoT devices connected to 6G will monitor soil conditions and help optimize water and fertilizer use.
Once 6G becomes ubiquitous, it will usher in a new era of sustainability-driven operations.
Industry standard metrics on deck: The industry will look to standardize sustainability measurements in 2024, including measuring the total carbon footprint of a wireless network. This will help avoid greenwashing claims and accelerate the drive to net zero.