As all organizations recognize they are (at least in part) software companies, questions arise. Which software development technologies have staying power? Which are just a flash in the pan? And which technologies, useful in the past, should now be retired in favor of better options?  Forrester studied 18 technologies used in software development that have been important contributors to software development efforts, are available commercially at enterprise scale, and have (or will have) enterprise traction:  Agile Planning/Metrics Tools Internal Developer Portals API Management Software Low-Code Development Platforms API Testing Tools Memory-Unsafe Languages Artifact Management Pure-Native Mobile Development Continuous Automation Testing (CAT) Platforms Serverless Computing DevOps Platforms Spatial Computing For Mixed/Augmented Reality Edge Development Platforms TuringBots For Coding, Delivery, And Testing Feature Management And Experimentation Solutions TuringBots For Software Analysis, Design, And Insights GraphQL Unmanaged Development Environments We categorized each technology into one of four quadrants, based on business value and maturity:  Experiment: Low maturity and low (current) business value.  Invest: Low maturity and high business value.  Maintain: High maturity and high business value.  Divest: High maturity and low business value.  You won’t be surprised that TuringBots (AI enhanced development) for coding, delivery, and testing wound up in the invest category. We think you should divest (slowly) memory-unsafe languages. You may be surprised where GraphQL ended up.  To see where all 18 software development technologies landed, and to better understand which technologies help software development teams satisfy the needs of their stakeholders, read The Forrester Tech Tide™: Software Development, Q4 2024.    Written with Caroline Bonde. source

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Ben Smith, chair of digital and analytics at global consulting firm Kearney, has witnessed several significant enterprise technology changes throughout his career. The first change came with the advent of the PC, followed by the client-server model, the HTTP browser, and the smartphone. As he surveyed the market at the end of 2024, he said the AI boom “is bigger than all of them.” “I think it’s going to lead to a lot of craziness, like we saw between ‘95 to ‘04,” Smith told TechRepublic, referencing the internet boom and the rise of Google. “So, from a vendor perspective, this is a unique time.” What’s in store for tech vendor competition in the age of AI? And what should organisations do about it? Smith and Anshuman Sengar,  Asia-Pacific’s lead for digital and analytics at Kearney, outlined key trends shaping the market into 2025. More must-read AI coverage The big forces shaping the future of enterprise AI Kearney’s experts argue five forces are shaping AI heading into 2025. A battle for regulatory advantage between large and small players Incumbent and regulatory capture occurs when established companies in a market use their influence over regulatory agencies to shape rules that favor existing business models and restrict competition. Regarding big players in the AI market, Smith explained that there is “a lot of effort to create fear in the market so that the incumbents are better positioned” into the future. While incumbents seek to reduce the chance of being disrupted by others moving more quickly, Smith said that regulatory agencies in the E.U. and U.S. are also showing “anti-acquisition” pushback. This may create an environment for start-ups and challengers to build businesses and grow rather than being acquired by larger organisations seeking to dominate. Sengar noted that there is potential for start-up innovation in the Asia-Pacific region at the application layer, building on the AI engines embedded into major platforms. He said local innovators, as do corporates like banks, through their own venture funds, have a role to play in competition with large global tech firms. A hunger for data centre semiconductor capacity for AI computing Smith said that society is experiencing the “largest off-cycle boom in semiconductor manufacturing fabrication facilities, or fabs, that we’ve seen in a long time.” Nationalism and governments are driving this surge, as many are building large data centres for AI computing. For AI users, this shift will cause “a massive decline in the next 12 to 24 months” in the cost of a token, making AI cheaper. In APAC, the drive for capacity results in large data centre transactions, such as private equity firm Blackstone’s acquisition of regional data centre company AirTrunk for AUD $24 billion. Sengar said companies across Asia are investing in data facility developments in Indonesia, and he expects India to launch its fab capability soon. A drive to understand, unpack, and use data for AI advantage Smith emphasised the importance of data in the emerging dynamics currently unfolding in the AI market. He noted that various players in the ecosystem are working to determine data ownership and usage in an AI context, whether the data resides within a company or externally. “I think the market is much more sophisticated this time as opposed to when the internet happened the first time,” Smith said. The unprecedented capital intensity funding the AI boom According to Smith, the capital intensity of AI — particularly in a high global interest rate environment — is a significant factor for technology players aiming to gain an advantage in the field. “If you look at the telco build out, or the fiber build out from ‘95 to 2002 … the amount of capital being deployed on GenAI data centers, swamps that by multiple factors. I mean, you will see data centres that cost hundreds of millions of dollars relative to the fiber build-outs we saw.” Smith predicts that, within the next few years, the world will see its first single data centre worth U.S. $1 trillion, which he expects to see built in either the U.S. market or in China. A geopolitical environment that is impacted by AI AI is connected to national economic security and national defense, making it different from previous technology innovations. Smith said this has created a “weird geopolitical environment,” with AI more of a political issue than the internet because of these national security implications. Three tips for navigating the forces shaping AI Kearney experts advise organisations to consider investing in and implementing AI based on their company and industry. Smith warns against getting caught up in the AI hype, while Sengar suggests data can be managed as a priority. 1. Avoid pursuing too many AI use cases Smith said one dangerous path is for enterprises to test every use case for AI. Instead, he said organisations should prioritise only those use cases that are most important for the business to pursue today. While some business use cases might be effective, they may also be much cheaper to do when the cost of an AI token decreases, so organisations would be better off waiting in some cases. 2. Will AI really will change your industry? Executive teams and boards should ask whether AI will fundamentally change the basis of competition in their industry. If it is, then they should move quickly, Smith said, giving the example of drug discovery and insurance markets, where he said AI is likely to dramatically impact how businesses compete. If it is not, he said investing heavily in AI, especially now at higher prices, may prove to be a mistake. 3. Do not wait to get control of your data Organisations can act immediately to take control of their data, whether they are pursuing AI heavily now or choosing to wait. Sengar said companies in APAC are struggling with their data, including customer data quality. “Getting control of your data, especially customer data, and ensuring you understand what you are capturing and that it is secure is something you

As we navigate through 2024 and gear up for 2025, we are witnessing a pivotal moment in technological evolution where two transformative forces—5.5G (also referred to as 5G-Advanced or 5G-A) networks and artificial intelligence (AI)—are converging to reshape our digital landscape. The commercial launch of 5.5G, coinciding with an extraordinary multiplying of AI applications, marks a watershed moment in technological history. With over three million AI-capable applications now developed globally, surpassing the total number of traditional apps available in app stores, we are entering an entirely new paradigm: the Mobile AI era. This convergence represents far more than the sum of its parts. While previous technological advances have incrementally improved our capabilities, the marriage of 5.5G and AI promises to fundamentally transform how we interact with technology, conduct business, and structure our societies. The implications of this transformation extend far beyond the telecommunications industry, touching every sector of the global economy and reshaping the fabric of our digital interactions. With the emergence of Mobile AI, we need to rethink our understanding of connectivity and computing power. Traditional boundaries between device capabilities and network infrastructure are blurred to create an ecosystem where intelligence is ubiquitous and seamlessly integrated. This new era brings forth unprecedented forms of human-machine interaction, spawning intelligent services previously confined to science fiction. The structural changes in traffic models and data consumption patterns we observe are the initial indicators of a more profound transformation underway. Telecoms as the foundation of the Mobile AI era Telecommunications carriers stand at the heart of this revolution, positioned as the crucial enablers of this new technological shift. Their evolution from traditional service providers to sophisticated technology companies (Techcos) represents a fundamental reimagining of their role in the digital ecosystem. Modern consumers increasingly demand services that are not only real-time and on-demand but also intelligent and predictive, expecting seamless integration across platforms and personalized experiences. Leading carriers worldwide have already demonstrated the remarkable potential of AI service capabilities on live 5.5G networks, showcasing applications that span personal use, smart homes, transportation systems, and enterprise operations. If telecommunication carriers are the heart, the integration of 5.5G or 5G-A technology is the soul that unleashes AI’s full potential in mobile environments. This provides the essential combination of high bandwidth, low latency, and massive connection density required to support advanced AI applications at scale. The sophistication of 5.5G networks enables real-time processing of complex AI algorithms, facilitating everything from autonomous vehicles to smart manufacturing systems. The recent development of “Mobile going AI,” where new service and business models are transforming mobile internet services, and “AI going Mobile”, where new mobile services like smart vehicles and robots create new momentum for both society and the mobile industry, particularly as 5.5G networks demonstrate their capability to support diversified connections, experiences, and services needed to address new requirements coming from AI agents, smart vehicles, and embodied intelligence. As the rapid development of these technologies accelerates the Fourth Industrial Revolution, AI emerges as a principal driver of global economic growth, transforming multiple markets simultaneously while creating new opportunities and disrupting traditional business models. Ammar Tobba, VP, Public Affairs & Communications, Middle East & Central Asia, Huawei Huawei Connecting underserved areas and driving digital economies The deployment of advanced 5G technologies, particularly Fixed Wireless Access (FWA), plays a transformative role in developing regional digital economies. These technologies are instrumental in bridging the digital divide and achieving meaningful connectivity goals, particularly in underserved areas where traditional infrastructure deployment has been challenging. The impact of this technological democratization extends far beyond simple internet access, enabling new forms of digital participation and economic opportunity. The impact of 5.5G or 5G-A technology spans multiple sectors, each with its transformative potential. In healthcare, it enables remote surgery and real-time patient monitoring. In education, it facilitates immersive learning experiences and personalized instruction at scale. In industrial applications, it powers smart factories and autonomous systems. The technology’s enhanced machine learning capabilities support extended reality applications, industrial IoT implementations, and precision agriculture initiatives, directly contributing to sustainable development goals while driving economic growth. The GCC region stands at the forefront of global 5G deployment, positioning itself to fully exploit 5.5G commercialization and its transformative use cases. This leadership is particularly significant given the proven correlation between ICT industry development and national economic growth. According to Huawei’s Global Digitalization Index (GDI), a one-US-dollar investment in digital transformation yields an impressive 8.3-US-dollar return in a country’s digital economy. This research, covering 77 countries representing 93% of global GDP and 80% of the world’s population, demonstrates the crucial role of ICT investment in building robust digital economies. The path to realizing the full potential of Mobile AI requires unprecedented collaboration among ecosystem stakeholders. Public-private partnerships are crucial in accelerating adoption and ensuring equitable access to these transformative technologies. Sharing knowledge, insights, and experiences among key players is essential for inspiring the next generation of digital transformation and achieving regional digital ambitions. Moving forward, it’s clear that the convergence of 5.5G and AI is a fundamental shift in how we approach digital transformation and sustainable development. The Mobile AI era promises to deliver not only economic benefits but also social and environmental improvements through more efficient resource utilization and intelligent system optimization. source

By Jonathan Capriel ( November 15, 2024, 6:56 PM EST) — Cruise LLC, the autonomous vehicles subsidiary of General Motors Co., has agreed to pay $500,000 in criminal fines to end claims that it made false statements to federal highway investigators by omitting that one of its vehicles dragged a pedestrian over 20 feet, according to an announcement by federal prosecutors…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

3LOD Is Risk Management’s Single Biggest Bottleneck It’s not you; it’s the model! The three lines of defense (3LOD) concept was initially developed as a corporate governance framework to implement segregation of duties requirements under the 2002 Sarbanes-Oxley Act. And in 2013, the Institute of Internal Auditors (IIA) promoted it as a solution to enhance risk management. But as anyone who has tried to implement it as a foundation for enterprise risk management will tell you, the 3LOD is not a model for managing risk. Instead, it defines, with ample rigidity, the roles required to comply with segregation of duties requirements. This division is conceptually simple but does not match the operating model at most organizations. For example, the first and second lines get blurred due to complex management structures that perpetuate silos, misalign incentives, and turn “risk management” into a compliance review gate. Stop Turning RISK Into A Dirty Four-Letter Word Conventional means of managing risk haven’t kept pace with the demand, velocity, or pressure that most enterprise risk teams face. Worse yet, many governance, risk, and compliance programs hyperfocus on compliance, completely ignore risk, and scramble to stand up governance for every new emerging risk, technology, or threat. The 3LOD model is not built to solve this. Some of the top reasons why we need a modern approach are that: Risk is dynamic. Risk is intrinsically linked to every decision we make, yet it’s difficult to predict because it’s uncertain and interconnected. Risk originates in three dimensions: 1) Systemic risk is external to the organization and beyond its control (e.g., climate, geopolitics); 2) ecosystem risk is external to the organization but within varying degrees of control (e.g., third parties, supply chain); and 3) enterprise risk is internal to the organization and directly controllable (e.g., cybersecurity, financial risk). Risk is continuous. Risks and opportunities evolve over time. Point-in-time, static risk assessments don’t reflect reality. Instead, teams require a continuous process to identify risk context, assess it as plans and objectives develop, make decisions, and monitor the results. Cyber risk is business risk. Today, technology powers every business process, which makes cyber risk a business risk. Typically, the chief risk officer and/or enterprise risk function selects the risk management model, while the CISO needs to ensure that the model is functional for the organization’s cybersecurity needs. Without working in lockstep, security and risk pros are stuck living in fear from audit to audit while foreseeable, preventable risk events materialize repeatedly. Introducing Forrester’s Continuous Risk Management Model Many orgs today do aspects of risk management — such as conducting assessments, implementing controls, remediating gaps, and/or reporting on progress — but they lack a defined lifecycle approach. This results in piecemeal tasks that create a false sense of assurance, poor stakeholder engagement, misused resources, and missed opportunities. The Forrester Continuous Risk Management Model is a blueprint for holistic risk management. Drawing on best practices in risk, strategy, and project management, the model outlines eight sequential phases (four pertaining to strategic planning and four related to business performance) that integrate key stakeholders, processes, data, and feedback for a value-based risk management approach. Forrester’s model equips teams with a framework to formalize their current risk management work, identify enhancements, and chart a path to maturity, because it: Bridges the gap between risk strategy and business performance. Strategy and performance are essential components of risk management, but risk teams struggle to integrate them. Why? They’re complex, context-sensitive, and require commitment across multiple layers of the business. Yet without them, business leaders lack the right insights and can’t be sure that they will meet their objectives, while risk and operations teams struggle to meet changing operational priorities. Is domain-agnostic, creating consistent risk management across the org. Risk pros can apply it within any area that requires risk and compliance management, such as information security, operational, third-party, and emerging risks. It provides a basis for standardization and consistency in the risk management process as well as for a common risk taxonomy across all risk management functions. Anchors itself to the pursuit of value. Risk management must consider the upside, not only the downside risk. Forrester’s model enables risk pros to accelerate their organization’s pursuit of value by establishing the appropriate context, evaluating trade-offs, and supporting decision-making that accelerates, rather than impedes, growth, innovation, and resilience. Creates on- and offramps for strategic decisions. Strategic decisions don’t always follow a linear path. In fact, opportunity or tragedy is just as much a part of timing as circumstance. In Forrester’s model, the risk decision is the initial approval, and the change management decision accounts for ongoing feedback and creates an onramp and offramp for investments and initiatives before they go horribly wrong or before the opportunity passes by. For an in-depth look at the model, Forrester clients can check out our report, No More Blurred Lines: Introducing Continuous Risk Management, and schedule an inquiry or guidance session with us to discuss how continuous risk management will benefit you. Learn More At The Security & Risk Summit If you want to learn more about continuous risk management and our new model, check out the agenda for our upcoming Security & Risk Summit, December 9–11 in Baltimore. Alla and I will be copresenting a keynote entitled “The Continuous Risk Revolution Is Here. Down With The Three Lines Of Defense!” See the agenda for more details, and we hope to see you in Baltimore. source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A new tool called AnyChat is giving developers unprecedented flexibility by uniting a wide range of leading large language models (LLMs) under a single interface. Developed by Ahsen Khaliq (also known as “AK”), a prominent figure in the AI community and machine learning growth lead at Gradio, the platform allows users to switch seamlessly between models like ChatGPT, Google’s Gemini, Perplexity, Claude, Meta’s LLaMA, and Grok, all without being locked into a single provider. AnyChat promises to change how developers and enterprises interact with artificial intelligence by offering a one-stop solution for accessing multiple AI systems. At its core, AnyChat is designed to make it easier for developers to experiment with and deploy different LLMs without the restrictions of traditional platforms. “We wanted to build something that gave users total control over which models they can use,” said Khaliq. “Instead of being tied to a single provider, AnyChat gives you the freedom to integrate models from various sources, whether it’s a proprietary model like Google’s Gemini or an open-source option from Hugging Face.” Khaliq’s brainchild is built on Gradio, a popular framework for creating customizable AI applications. The platform features a tab-based interface that allows users to easily switch between models, along with dropdown menus for selecting specific versions of each AI. AnyChat also supports token authentication, ensuring secure access to APIs for enterprise users. For models requiring paid API keys—such as Gemini’s search capabilities—developers can input their own credentials, while others, like basic Gemini models, are available without an API key thanks to a free key provided by Khaliq. How AnyChat fills a critical gap in AI development The launch of AnyChat comes at a critical time for the AI industry. As companies increasingly integrate AI into their operations, many have found themselves constrained by the limitations of individual platforms. Most developers currently have to choose between committing to a single model, such as OpenAI’s GPT-4o, or spending significant time and resources integrating multiple models separately. AnyChat addresses this pain point by offering a unified interface that can handle both proprietary and open-source models, giving developers the flexibility to choose the best tool for the job at any given moment. This flexibility has already attracted interest from the developer community. In a recent update, a contributor added support for DeepSeek V2.5, a specialized model made available through the Hyperbolic API, demonstrating how easily new models can be integrated into the platform. “The real power of AnyChat lies in its ability to grow,” said Khaliq. “The community can extend it with new models, making the potential of this platform far greater than any one model alone.” What makes AnyChat useful for teams and companies For developers, AnyChat offers a streamlined solution to what has historically been a complicated and time-consuming process. Rather than building separate infrastructure for each model or being forced to use a single AI provider, users can deploy multiple models within the same app. This is particularly useful for enterprises that may need different models for different tasks—an organization could use ChatGPT for customer support, Gemini for research and search capabilities, and Meta’s LLaMA for vision-based tasks, all within the same interface. The platform also supports real-time search and multimodal capabilities, making it a versatile tool for more complex use cases. For example, Perplexity models integrated into AnyChat offer real-time search functionality, a feature that many enterprises find valuable for keeping up with constantly changing information. On the other hand, models like LLaMA 3.2 provide vision support, expanding the platform’s capabilities beyond text-based AI. Khaliq noted that one of the key advantages of AnyChat is its open-source support. “We wanted to make sure that developers who prefer working with open-source models have the same access as those using proprietary systems,” he said. AnyChat supports a broad range of models hosted on Hugging Face, a popular platform for open-source AI implementations. This gives developers more control over their deployments and allows them to avoid costly API fees associated with proprietary models. How AnyChat handles both text and image processing One of the most exciting aspects of AnyChat is its support for multimodal AI, or models that can process both text and images. This capability is becoming increasingly crucial as companies look for AI systems that can handle more complex tasks, from analyzing images for diagnostic purposes to generating text-based insights from visual data. Models like LLaMA 3.2, which includes vision support, are key to addressing these needs, and AnyChat makes it easy to switch between text-based and multimodal models as needed. For many enterprises, this flexibility is a huge deal. Rather than investing in separate systems for text and image analysis, they can now deploy a single platform that handles both. This can lead to significant cost savings, as well as faster development times for AI-driven projects. AnyChat’s growing library of AI models AnyChat’s potential extends beyond its current capabilities. Khaliq believes that the platform’s open architecture will encourage more developers to contribute models, making it an even more powerful tool over time. “The beauty of AnyChat is that it doesn’t just stop at what’s available now. It’s designed to grow with the community, which means the platform will always be at the cutting edge of AI development,” he told VentureBeat. The community has already embraced this vision. In a discussion on Hugging Face, developers have noted how easy it is to add new models to the platform. With support for models like DeepSeek V2.5 already being integrated, AnyChat is poised to become a hub for AI experimentation and deployment. What’s next for AnyChat and AI development As the AI landscape continues to evolve, tools like AnyChat will play a crucial role in shaping how developers and enterprises interact with AI technology. By offering a unified interface for multiple models and allowing for seamless integration of both proprietary and open-source systems, AnyChat is breaking down the barriers that

News influencers – People who regularly post about current events and civic issues on social media and have at least 100,000 followers on any of Facebook, Instagram, TikTok, X (formerly Twitter) or YouTube. Political orientation – A measure of a news influencer’s partisan or ideological views. A right-leaning news influencer is one who publicly expresses that they identify as a Republican or conservative or support Donald Trump in the 2024 presidential election. A left-leaning news influencer is one who publicly expresses that they identify as a Democrat, liberal or progressive or support Vice President Kamala Harris (or supported President Joe Biden before he dropped out of the race) in the 2024 election. This information was found in the bio, profile picture, banner image, pinned posts or recent posts on an influencer’s social media account, any personal website or professional page, and prominent media coverage. Values and identities – Language or imagery in the bio, profile picture, banner image or pinned posts on an influencer’s social media account that expresses specific beliefs or identities. News organization affiliation – An influencer with this affiliation is one who either currently works for or previously worked for a news organization, as well as freelancers who have regularly contributed to news organizations. A news organization can be any news outlet that has a staff and multiple bylines. Researchers considered affiliated influencers to have this background regardless of their news organization’s political orientation, audience size or primary publishing method (digital, TV, print, etc.). Major social media sites – The five primary sites we studied, chosen based on audience size and the presence of discussion about news: Facebook, Instagram, TikTok, X (formerly Twitter) and YouTube. A somewhat higher share of news influencers on the social media site X explicitly identify with the political right (28%) than the left (21%). A small share (3%) express some other political affiliation, while about half (48%) do not express any clear political lean. Influencers were categorized by whether they identify with a political party or ideology or expressed support for the Democratic or Republican presidential candidate in their social media profile, posts, personal website or media coverage. About this chapter This chapter looks at news influencers on X (formerly Twitter). Virtually all of them also have accounts on other sites. For analysis of news influencers in general across social media sites, read the report overview. In this report, news influencers are people with large followings on social media sites who regularly post about current events or civic issues. Refer to the methodology for details. Related: X users’ experiences with news Fewer news influencers on X identify specific values or identities on their accounts. This includes 6% who say they are pro-LGBTQ+ (or express a LGBTQ+ identity), 4% who express a pro-Palestinian viewpoint and 3% who identify as pro-Israeli. In addition, 3% of X news influencers express views favoring Ukraine. These positions can be indicated in a variety of ways, whether through words, images or emojis (including flags). Some X news influencers also prominently identify as opposing (2%) or supporting abortion rights (fewer than 1%). Among news influencers posting on X, 64% are men, while 29% are women. Previous research has found that 64% of Americans who regularly get news on X are men, while 35% are women. Refer to the methodology for details on how researchers coded news influencers by gender. Most news influencers on X have not worked for a news organization, but about a quarter (26%) have a current or former affiliation with a news outlet. These organizations range from more traditional news outlets like CNN to newer digital news sources such as The Daily Wire. For more details on the differences between influencers who have worked for a news organization and those who have not, read Chapter 4. What are news influencers on X posting about? To get a sense of what news influencers are posting about, researchers collected and analyzed all public posts by the 500 news influencers in our sample for three separate weeks: July 15-21, July 29-Aug. 4 and Aug. 19-25. There were many major events related to the election in or around these weeks, including the first assassination attempt on Donald Trump on July 13, the Republican National Convention July 15-18, President Joe Biden’s withdrawal from the race July 21 and the Democratic National Convention Aug. 19-22. More than half of X posts by news influencers that were about current events or civic issues during those weeks addressed politics or the election (55%). Social issues were the focus of 18% of all news-focused posts, covering a range of topics from race to abortion to LGBTQ+ issues to the culture wars. And 15% of posts were about international topics, with about half of these covering the Israel-Hamas war (8%). What other sites are X news influencers on? Although a higher percentage of news influencers are on X than any other social media site, most news influencers on X are also on at least one other site. About a third of news influencers on X (34%) are only on X, while about two-thirds are on at least one other site. This includes 31% who are on four or more other social media sites (five or more in total). Roughly half of news influencers on X are also on Instagram (49%), while smaller shares are on YouTube (44%), Facebook (35%) and TikTok (21%). The study also looked at how many news influencers on each site host a podcast or a newsletter. Roughly a third of news influencers on X (37%) host a podcast, while one-quarter send out an email newsletter. A majority (62%) also seek financial support from their audience in at least one way. This includes 52% who offer subscriptions to additional content (some through subscription tools that X provides), 32% who ask for donations, and 23% who sell merchandise. A relatively small share of X news influencers (6%) also have a public Discord server where they can further connect with fans and followers. source

Customers expect seamless, efficient, 24/7 support. that level of contact center CX is table stakes for maintaining a positive brand image for today’s buyers. Providing a high-level contact center customer experience requires more than just quick responses — it demands thoughtful integration of technology, well-trained agents, and personalized service. This post will explore practical strategies to enhance CX across the board. I’ll focus on actionable steps you can take to create a more efficient, personalized, and secure experience for customers. 1 RingCentral Office Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Medium (250-999 Employees), Enterprise (5,000+ Employees), Large (1,000-4,999 Employees) Medium, Enterprise, Large Features Hosted PBX, Managed PBX, Remote User Ability, and more Zero-spend ways to improve contact center CX These changes can streamline processes, reduce friction, and ultimately enhance customer satisfaction. Chances are, you have most of the tools you need to accomplish these strategies already. If you have to go out and invest in better contact center technology, so be it, but I’d try these cost-effective strategies first. 1. Support and empower your agents Burnout is common in contact centers, and attrition is high. So anything you can do to support your agents helps, and it’ll likely trickle down to improve your customer experience. SEE: Learn about the most pressing causes of call center burnout and how to fix them.  Regular and comprehensive training is the best way to support agents. Having experienced team members share tips in peer-to-peer training sessions is a beneficial and engaging way to build comradery amongst team members. I know that time is precious in a contact center. Pulling veteran agents away from their desk to talk with rookies isn’t always feasible. Consider using recorded calls to train agents where they listen to examples of good and bad customer service. Focus specifically on the customer experience and frame the lesson around how to improve it. In addition to training, see what you can do to help your agents work-life balance. This is one of the top reasons people will stay with an employer. Is it possible to offer flexible scheduling? Have you created a perfect PTO policy and created a culture where managers encourage employees to actually use their time off? When agents feel valued and well-equipped, they’re more likely to provide better service. Training, proper tools, and a positive work environment help agents handle customer issues more efficiently and empathetically, which leads to faster resolutions and higher customer satisfaction. When agents are confident in their role, they can focus on solving problems rather than struggling with limited resources or burnout, ultimately benefiting both the customer and the business. 2. Survey your customers Consider low-cost feedback mechanisms, like email follow-ups or quick phone surveys. These simple post-interaction surveys can provide valuable insights into customer satisfaction. Yes, you can spend a ton of money on customer surveys, but you can also get useful data by being scrappy. Basic analysis of customer feedback can be done manually or with standard office software. Over time, you’ll identify common themes, sticking points, and areas of concern. That said, for high-volume contact centers, investing in specialized call center quality assurance software might be justified. These tools can automate and streamline the feedback analysis process, providing real-time insights that are crucial for larger operations. SEE: Learn about critical call center quality assurance best practices.  But for smaller or medium-sized centers, manual methods and basic tools can be surprisingly effective in capturing and utilizing customer feedback to refine your CX strategy. 3. Streamline IVR menus Improving your customer experience could also begin the moment customers reach out to your contact center. How? By streamlining your Interactive Voice Response (IVR) system. A well-designed IVR menu can significantly improve customer experience. To streamline your IVR menus: Assess current IVR effectiveness: Start by evaluating your current IVR system. Identify points where customers frequently get stuck or opt to exit the IVR to speak to an agent. Analyzing call logs and dropout rates can provide insights into which parts of the menu are causing frustration. Simplify menu options: Experiment with reducing the number of options in each menu to avoid overwhelming your callers. Focus on the most common reasons customers call and ensure these are addressed early in the menu. Make sure you’re using clear, concise language. Prioritize quick resolution paths: Arrange the menu options in a way that the most frequently selected choices are presented first. If certain queries can be resolved without agent intervention, such as account balance inquiries or payment confirmations, make those options readily available. Regular updates based on feedback: Going back to our last tip, continuously gather feedback on the IVR system, both from customers and your agents. Use this feedback to make regular adjustments. For example, if a new product or service is leading to an increase in calls, update the IVR prompts to address this immediately. Test and iterate: Implement changes in stages and monitor their impact. You can experiment with A/B testing different versions of the IVR menu to determine which is more effective in improving caller experience and reducing call handling times. Along with these tactics aimed at improving CX, contact centers should run regular IVR testing to ensure that their system is fully functional, secure, and able to withstand spikes in traffic. SEE: Understand automated IVR testing and explore five IVR testing tools to help you get started.  4. Implement effective call routing Optimizing call routing in your contact center can go a long way toward improving CX. By ensuring that customers are connected with the most appropriate agent or department, you can reduce wait times and increase the likelihood of first-call resolution. Here’s how to maximize the effectiveness of your call routing. Analyze call patterns: Start by analyzing the types of calls your center receives. Are there patterns, peak times, or common queries? This analysis will help you understand how to categorize calls and route them more efficiently. Skill-based routing: Implement skill-based routing by assigning calls

By Jeff Montgomery ( November 15, 2024, 4:19 PM EST) — An investor in a “public benefit” company that provides sensitive software to government agencies and allies sued the business Friday in Delaware Chancery Court, seeking documents on a stock purchase agreement and other moves purportedly made without required consents…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source