With modest GDP growth and stagnant budgets, organizations around the world are finding it necessary to reallocate funds from mature areas to support IT investments. While cloud and security continue to be key priorities, generative AI (GenAI) is increasingly taking the spotlight as companies strive for significant productivity improvements. GenAI investment is expected to grow 30%, with leaders from companies with high GenAI maturity anticipating their return on investment will be three-times higher over the next three years than that of companies with little or no adoption of the technology, according to a new report by Boston Consulting Group (BCG) released today.

Silent Sector, a leading cybersecurity firm specializing in protecting mid-market businesses, has discovered a major flaw in the two-factor authentication (2FA) enrollment process that could leave millions of organizations vulnerable to cyberattacks. The vulnerability lies in the use of QR codes for 2FA, a common security practice across industries, and poses an urgent threat to the security of organizations that rely on this method to protect sensitive accounts.

The 2024 ISG Provider Lens™ global Specialty Analytics Services report for the supply chain industry finds that organizations are investing in technologies to harness enterprise and ecosystem data for better decision-making. The COVID-19 pandemic exposed the fragility of global supply chains, so enterprises are exploring how data and analytics can make systems more resilient and sustainable.

“Companies can no longer take supply chains for granted,” said Bob Krohn, partner, manufacturing, for ISG. “By implementing new technologies with providers, they are achieving the end-to-end visibility they need to stay ahead of changes.”

A significant exposure related to the use of QR codes in two-factor authentication (2FA) processes has been identified and reported to the Internet Engineering Task Force (IETF) by researchers and analysts at Silent Sector (https://silentsector.com), a cybersecurity services company that specializes in providing tailored risk management solutions to mid-market and emerging companies across various industries, including healthcare, financial services, technology, manufacturing, and defense.

Last month, CIO.com hosted a virtual roundtable featuring top technology executives from industries including insurance, healthcare, banking, real estate, and manufacturing. The event, supported by experts from IBM, centered around the evolving role of mainframe platforms in supporting AI-enabled enterprises, particularly in the context of modernization and business transformation. As artificial intelligence (AI), and more specifically generative AI (GenAI), continues to reshape industries, enterprises are revisiting their mainframe systems to better align with this new wave of technological innovation.

Despite prevailing conventional wisdom in the enterprise technology community, businesses can drive innovation without being overwhelmed by the complexities of legacy system modernization, according to Tiago Azevedo, CIO of OutSystems, a leader in low-code and no-code (LCNC) technology. These LCNC platforms –  when combined with generative AI (GenAI) – can allow organizations to innovate rapidly and deliver immediate business value without the need for extensive legacy overhauls.

There are six technologies that will have transformational benefits within five years for digital government services, according to Gartner, Inc. These include digital employee experience (DEX), AI code assistants, generative AI (GenAI), generative design AI, predictive analytics in government and workstyle analytics.

“Delivering services digitally continues to be a priority in government transformation plans,” said Daniel Snyder, Sr Director Analyst, KI Leader at Gartner. “These technologies will help government CIOs bridge the gap between digital innovation goals and executing against strategy objectives. Collectively, they will be a crucial element for executives in aligning technology innovation to mission outcomes to keep pace with growing citizen expectations.”

Generative AI (GenAI) is creating a new type of knowledge worker who can code faster and summarize documents instantly. But can the tool also enable people to meet the shifting demands of their roles? A new scientific experiment conducted by the BCG Henderson Institute in collaboration with BCG X and Emma Wiles from Boston University, as described in GenAI Doesn’t Just Increase Productivity. It Expands Capabilities., examines what happens when, instead of using GenAI to improve performance within their current skillset, people use the technology to complete tasks beyond their existing capabilities.

The ISG Buyers Guide™ for Cloud-Native AI and Data Platforms, produced by ISG Software Research, projects that through 2026, more than one-third of enterprises will deploy cloud-native AI and data platforms in their information architectures. Most leading cloud providers offer both AI and data capabilities, while independent software providers offer AI and data platforms built to operate natively in and across cloud environments, the report says.

The report points out that AI requires large amounts of high-quality data that needs to be prepared, engineered and organized to feed and train AI models. The volumes of data necessary for accurate AI models place a significant demand on computing resources, which can often be best met with elastic cloud platforms. The cost of these systems can be significant, and any inefficiencies in the process can exacerbate the costs, the report says.

A recent Gartner, Inc. poll of more than 1,800 executive leaders, revealed that 55% of organizations have an AI board. The poll also indicated 54% of organizations have a head of AI or an AI leader that orchestrates activities.

“The findings show that organizations are divided regarding if an AI board is necessary,” said Frances Karamouzis, Distinguished VP Analyst Gartner. “The answer is yes, enterprises need an AI board to transcend the multidisciplinary challenges to drive value and reduce risk. However, the duration, scope, and resourcing is context-specific and use-case dependent. For some, it’s a short-term, stopgap measure. For others, it’s a longer-term change to their operating model.

Only 14% of customer service and support issues are fully resolved in self-service, according to a survey by Gartner, Inc. Even for issues that customers describe as “very simple”, only 36% resolve fully in self-service.

While many organizations have made considerable investments in self-service capabilities, a Gartner survey of 5,728 customers conducted in December 2023 revealed that resolution rates remain low.

The 5G RedCap, finalized in Release 17, provides a migration pathway from 4G LTE to 5G for mid-range devices, particularly suitable for IoT. ABI Research forecasts 80 million IoT RedCap module shipments from 2024 to 2029. RedCap simplifies device complexity, providing an affordable pathway to 5G for IoT device OEMs. It delivers LTE-equivalent throughput performance and draws significant interest across the IoT value chain.

Edge computing plays a crucial role in reducing latency and enhancing privacy as the focus of AI shifts from training to inference. This facilitates faster decision-making with reduced network congestion. Global spending on edge computing is projected to reach $228 billion in 2024 and $378 billion by 2028

According to a new KPMG report, risk management is increasingly challenging. The survey found that 61% expect a significant increase in their level of responsibility for risk in the next three to five years. The research revealed that risk management professionals are focused on adapting to new risk types such as AI, ESG, and cyber risk.

Global end-user spending on information security is projected to reach $212 billion in 2025, a 15.1% increase from 2024. This surge is attributed to the heightened threat environment, cloud migration, and talent shortages, prompting organizations to prioritize security and increase spending. Adopting AI and GenAI drives investments in security software markets, with a projected 15% increase in cybersecurity resources required to secure it through 2025.

Artificial intelligence (AI) and its integration into enterprise systems are driving a resurgence of on-prem computing. In a recent CIO.com virtual roundtable co-hosted by IBM's Wayne Derry, senior enterprise technology executives from across the country explored the challenges and opportunities presented by this shift, particularly for organizations that previously embraced a "scorched earth" approach by eliminating their data centers.

One of the biggest problems facing business leaders in the era of AI may well be their tendency to have a deterministic perspective. Deterministic thinking among company executives can be considered a holdover from decision-making styles that became prevalent during the industrial era when the emphasis was on efficiency, standardization, and predictability, which were critical in managing large-scale, repetitive processes. Indeed, businesses were often thought of -- and described -- as machines that built the products and services they brought to market.

Mimecast's recent report highlights malicious links and AI-driven bots in call centers as major cybersecurity threats. The report reveals a significant spike in the use of malicious links, with attackers increasingly using multiple layers of false information to bypass security measures.

Worldwide spending on AI, including AI-enabled applications, infrastructure, and related services, is expected to double by 2028, reaching $632 billion, with a 29.0% compound annual growth rate. Organizations are leveraging AI for employee experience, customer engagement, business process, and industry innovations. GenAI investments are rapidly growing and expected to reach $202 billion, representing 32% of overall AI spending.