About seven-in-ten Americans surveyed in September (69%) say they are following news about the presidential candidates for the 2024 election very (28%) or fairly (40%) closely. More people say they are tuning in to election news as Election Day gets closer. In April, 58% of U.S. adults said they were following the election at least fairly closely, and by July, that number had risen to 65%. Attention in 2020 also increased closer to that election. A survey conducted in late August and early September 2020 found that 66% of Americans said they were very or fairly closely following news about candidates Joe Biden and Donald Trump, while in late September and early October 2016, 74% of respondents were following news about Trump and Hillary Clinton. This year, the rise in attention to the election has been driven by Democrats. While Republicans and independents who lean toward the GOP were somewhat more likely than Democrats and Democratic leaners to be following the election at least fairly closely in April and July, the two parties are now about equally likely to say they are following news about the candidates very or fairly closely (70% vs. 71%, respectively). The July survey was conducted July 1-7, before Biden announced his withdrawal as the Democratic candidate on July 21. On Aug. 5, Vice President Kamala Harris was confirmed as his replacement. Older Americans are paying much closer attention to election news than are younger adults, mirroring patterns in overall attention to news. About half of U.S. adults ages 18 to 29 (53%) say they are following news about the candidates at least fairly closely, compared with 85% of those ages 65 and older. And older adults are nearly four times as likely as Americans under 30 to say they’re following election news very closely (46% vs. 12%). The 2024 campaign events that Americans have heard or read about most In a 2024 presidential campaign season that has seen a number of major and dramatic events, three of them stand out in terms of the public’s exposure to that news. Fully 70% of U.S. adults say they have heard or read a lot about Harris replacing Biden as the Democratic presidential candidate. Close behind is the July 13 assassination attempt on former President Donald Trump during a Pennsylvania rally, with 66% saying they have heard a lot about that. (The survey questions were finalized before the second assassination attempt on Trump in September.) Finally, reinforcing reports of a large viewing audience, 64% of Americans say they heard a lot about the Sept. 10 ABC debate between Trump and Harris. Much smaller shares say they have heard or read a lot about several other topics mentioned in the survey. These include the vice presidential candidates, Republican JD Vance (36%) and Democrat Tim Walz (32%); the Democratic (29%) and Republican (24%) National Conventions; and third-party candidate Robert F. Kennedy Jr. endorsing Trump when he withdrew from the race (22%). Still, large majorities say they have heard at least a little about each of these topics. Similar shares of the two parties say they have heard or read a lot about the first attempted assassination of Trump in July. But on each other campaign topic measured by the survey, there are partisan differences in how much people have heard. For instance, Democrats are more likely than Republicans to say they have heard or read a lot about Harris replacing Biden as the nominee (76% vs. 67%). And the gap is larger when it comes to the debate between Harris and Trump, with 72% of Democrats saying they heard a lot about it, compared with 58% of Republicans. Democrats also are more likely than Republicans to have heard a lot about not only Walz (41% vs. 25%) but also Vance (41% vs. 34%). Four-in-ten Democrats say they heard or read a lot about the Democratic National Convention, compared with 21% of Republicans who say the same. Republicans are more likely than Democrats to say they heard a lot about the Republican National Convention, but the gap is smaller (29% vs. 20%). Republicans are modestly more likely than Democrats to say they have heard or read a lot about Kennedy endorsing Trump when he dropped out of the race (27% vs. 19%). What Americans want in campaign coverage – and what they actually see The survey asked respondents what kinds of news about the presidential candidates they are most interested in seeing. Topping the list is news about the candidates’ stances on issues, with 75% of U.S. adults saying they are extremely or very interested in this. 60% are extremely or very interested in the candidates’ moral characters. About half are highly interested in the candidates’ career experiences and their actions and comments on the campaign trail (49% each). 42% express high levels of interest in who is leading the race. And trailing far behind, only 14% say they are extremely or very interested in the candidates’ personal lives. Democrats and Democratic-leaning independents are considerably more likely than Republicans and GOP leaners to be highly interested in the candidates’ moral characters (69% vs. 52%). The survey also asked which of these six types of election news Americans see most often, and the top areas of interest for Americans do not always line up with what they are actually seeing the most news about. By far, the leading topic seen by Americans is news about the candidates’ actions and comments on the campaign trail: 40% say they see the most news about this, even though it is not among the top two topics in terms of interest. Smaller shares say they see the most news about the candidates’ stances on issues (17%), the candidates’ moral characters (14%) or the political horse race (13%). Just 8% say the most common type of election news they see involves the candidates’ personal lives, while 3% most often see news about the candidates’ career experiences. source

Skills form the basis for developing and defending new value propositions. Hence, being able to attract and retain top talent is a strategic priority. Having access to the right skills is business-critical, yet Forrester surveys underline that a majority of organizations are struggling with skills shortages. The employer brand can help with that; it influences a candidate’s decision to join, and stay with, an organization. Thus, the employer brand, representing the identity and reputation of an organization as an employer, plays a valuable role in closing skills gaps. Moreover, the employer brand and how it’s experienced by employees is an important factor for the quality of employee engagement after the hire. Our latest research helps business leaders align employee value proposition (EVP) and employer brand. Your employer brand is your public perception and reputation in the market, needed for attracting and retaining skills. When an organization’s words match employees’ lived experiences at work, recruitment and retention rates improve. Employer branding can be a differentiator to attract ideal candidates and skills to your organization. Your EVP, meanwhile, is the narrative that informs employees and candidates of what your organization can uniquely offer as an employer and what it expects in return. Nonauthentic promises and wishful thinking undermine your EVP — employees see through them and there’s then risk for growing friction between employer and employee expectations. Our report, What Your Company Means To Your Workforce Matters For Your Talent Strategy’s Success, helps business leaders understand how to synchronize the EVP and the employer brand to overcome skills shortages, among other things. Our research includes best practices for facilitating this alignment and: Identifies the key components that contribute to a compelling employer brand. Evaluates the effectiveness of the employer value proposition for employer branding. Examines the role of the employer brand in shaping the overall employee experience. Outlines steps to align EVP and employer brand. source

In the rapidly evolving landscape of technology, Artificial Intelligence has emerged as a beacon of innovation, with companies looking to increase operational efficiency, cost savings and improve employee productivity through AI initiatives. AI and Generative AI Spending Across the Globe IDC has recently unveiled the latest release of its Worldwide AI and Generative AI Spending Guide, 2024 V2. Presently, the global Artificial Intelligence market stands at nearly $235 billion, with projections indicating a rise to over $631 billion by 2028. The three leading industries in terms of Artificial Intelligence spending are Software and Information Services, Banking, and Retail. Combined, these sectors are projected to allocate approximately $89.6 billion towards AI in 2024, representing 38% of the global AI market. With an impressive five-year Compound Annual Growth Rate (CAGR) of 27%, their collective investment is anticipated to surge to nearly $222 billion by 2028. Notably, Generative AI accounts for more than 19% of the total investment across these three industries, highlighting its growing significance in the AI landscape. Worldwide AI and Generative AI Spending by Industry Source: IDC’s Worldwide AI and Generative AI Spending Guide, August (V2 2024) Industries Key Highlights in Artificial Intelligence The Software and Information Services industry is known for its dynamic nature and rapid growth, is now at the forefront of integrating Artificial Intelligence to revolutionize how services are delivered and consumed. With a spending of $33 billion in 2024, companies are using AI to make the software development lifecycle more efficient and error-resistant through AI lifecycle software and predictive models. Enhancing information services by personalizing content delivery based on user data, thus improving user engagement. Artificial Intelligence is also driving innovation by creating new products and tools for data analysis and market trend prediction, helping businesses stay competitive. Additionally, AI is augmenting and automating operational processes, increasing efficiency, and reducing costs by allowing functions such as human resources to focus on strategic tasks. This comprehensive integration of AI is not only streamlining operations but also fostering the development of high-quality, adaptive software and services. The Banking industry, a market with approximately $31.3 billion in investments in AI in 2024, is using the technology to enable banks to offer personalized customer experiences through machine learning and data analytics, allowing banks to tailor services to individual preferences. AI-powered chatbots and virtual assistants provide round-the-clock assistance for both basic and complex tasks, improving customer service and allowing human representatives to focus on intricate issues. Robotic Process Automation (RPA) streamlines back-office operations, reducing costs and errors. AI algorithms enhance fraud detection and risk management by analyzing transaction patterns and customer behavior for real-time action, thus protecting assets and building trust. In investment banking, AI-driven algorithmic trading analyzes market data for quick, strategic trading decisions, while AI also improves risk assessment models by predicting market shifts, aiding in informed investment decisions and risk management. Spending in AI for the retail industry is reaching around $25 billion in 2024. Artificial Intelligence is revolutionizing the retail industry by creating personalized shopping experiences through machine learning and data analytics, enabling retailers to understand and cater to individual customer preferences. This leads to enhanced customer engagement and loyalty with customized product recommendations and targeted marketing. AI also addresses inventory management challenges by predicting demand patterns and optimizing stock levels, reducing overstock and stockouts. AI-powered chatbots and virtual assistants improve customer service by handling inquiries efficiently, enhancing customer satisfaction. Additionally, in physical stores, Artificial Intelligence enhances the shopping experience with technologies like smart mirrors for interactive advertisements, promotion and product information and AI-driven systems for improved store security and layout optimization. Regional Outlook in Artificial Intelligence In both the Americas and EMEA regions, the banking industry emerges as the top spender in Artificial Intelligence, with market sizes estimated at approximately $19 billion and $8 billion for 2024, respectively. These markets are experiencing robust growth, with five-year Compound Annual Growth Rates (CAGRs) of 30% and 32%. Conversely, in the Asia-Pacific and Japan (APJ) region, the Software and Information Services Industry takes the lead in AI investments, boasting a nearly $11 billion market size, characterized by early and rapid adoption of certain AI technologies. A common trend across all three regions is the relatively low AI spending in the agriculture and fishing industry, marking it as the industry with the least investment in AI technologies. Conclusion The integration of Artificial Intelligence across various industries is not just a trend but a transformative shift that is reshaping the landscape of business, technology, and customer interaction. From retail to banking, software and information services to healthcare, AI is enhancing efficiency, personalizing experiences, and opening new avenues for innovation and growth. It’s clear that AI’s potential to drive operational excellence, understand and predict consumer behavior, and innovate product development is unparalleled. As industries continue to harness the power of AI, IDC continues to follow this journey closely and offers the latest insights in about AI and Generative AI spending across the globe. Learn more about IDC’s AI and GenAI Spending Guide by downloading this product overview. Find out what matters most to your customers with IDC’s AI Use Case Discovery Tool. Contributing Author: Mariana Fang – Research Analyst, Data & Analytics source

We’ve been talking a lot about the security challenges with artificial intelligence at Forrester, specifically with generative AI (genAI). We’ve researched the buzz on AI PCs and think 2025 is when they’ll start to gain adoption. But what about mobile? Leading vendors such as Google and Samsung, as well as secondary players like OnePlus and Xiaomi, have already released local AI engines for their Android phones, while Apple has announced its Apple Intelligence offering that will be previewed this fall — not to mention the mobile assistants like Alexa, Bixby, Google, or Siri that use AI or the growing list of apps that involve various AI engines and large language models. As an enterprise security leader, how can you control these AI engines on your organization’s managed mobile devices? Right now, it’s a mix of good and not so good. On the not-so-good side, there are limitations on what can be disabled through unified endpoint management (UEM) platforms. Local AI engines on Android devices cannot currently be managed through UEM, and as of this writing, UEM vendors are unsure of what will be available to manage Apple Intelligence. OS developers Google and Apple, along with device manufacturers who customize the Android OS for their platforms such as Samsung, OnePlus, or Xiaomi, have not released the information that UEM vendors require to code this configuration option into their platforms. Administrators can block an on-device app package though. Being that Google Gemini Nano, for example, uses com.google.android.aicore, this associated package can be blocked through a manual app blocking and that would suffice. The news is better for AI assistants, which can be disabled through UEM settings or, as with Alexa, by disabling the application. This feature has been available for some time. Security pros who may be concerned about business data being leaked should understand how those AI assistants interact with business applications, messaging, and audio/video channels on corporate and personal devices and adjust the UEM settings accordingly to limit the risk. For other applications that may collect data to send off to third parties for processing, modern mobile threat defense (MTD) solutions can analyze applications on mobile devices and let security analysts know where the application data is going. Security teams can then determine risk levels for the apps and devices and either disable access to corporate resources until the risky applications are removed, in the case of bring-your-own-device situations, or apply UEM policies to disable these applications for corporate devices. The range of threats targeting mobile devices is quite extensive, and as AI is integrated into more applications and platforms, security pros will need to implement more controls to reduce the risk of sensitive data being compromised. For mobile, the OS developers such as Apple and Google along with the platform vendors all need to allow UEM platforms to implement policies on managed devices to limit the corporate data that gets collected by AI and allow MTD vendors insight so they can better secure the mobile ecosystem. Forrester customers who have questions or concerns about mobile security within their enterprise should reach out to schedule an inquiry or guidance session with me to review how you can better protect your business resources. source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Do you use ChatGPT regularly? Do you have the “memory” feature turned on — which allows the chatbot from OpenAI to recall important information about you and your preferences? If so, navigate over to it when you have a free moment and enter in the following question: “From all of our interactions what is one thing that you can tell me about myself that I may not know about myself?” The question was proposed and suggested first on the social network X by Tom Morgan, founder of The Leading Edge newsletter and former director of client communications and marketing at Sapient Capital wealth management. The answers ChatGPT provides in response to this prompt may surprise and even move you in their insight into your character and work style. Presumably, it could work with other AI chatbots and assistants with persistent memory, such as Anthropic’s Claude Sonnet 3.5. For example, here’s what it responded when I asked it this very question (using the GPT-4o model, the default paid one). Other users have reported similarly, moving, insightful responses. Even OpenAI co-founder and CEO Sam Altman remarked on the trend on his account on X, stating “love this” and quote posting Morgan’s original post. Yet others, such as AI researcher and expert Simon Willison, disagree that the trend reveals anything particularly insightful about the user. Posting on X as well, Willison likened the responses to a “horoscope generator.” However, I disagree with this take as at least in my case — and presumably for all those who have ChaGPT’s memory feature enabled (read how to turn it on here) — the chatbot is taking into account whatever is stored in its memory to answer you, and even if it does not derive insights from every single interaction you have with it, it clearly knows information about you that it can use to attempt some sort of value-judgement and introspective answer (as evidenced by the fact that my response noted I was a journalist). Still others have posted variations on the original question proposed by Morgan, noting the curious user would do well to check out the variation in responses by switching the underlying model powering ChatGPT from the default GPT-4o or 4o mini to OpenAI’s new o1 preview reasoning model. Others have altered the prompt to receive brutal criticism and honesty. And still others have completely other ideas for questions you could ask the chatbot, such as requesting it “roast” you in the style of a Comedy Central special. Regardless of which style question you decide to ask ChatGPT, or any AI chatbot for that matter, regular users might find it interesting, amusing, and potentially revealing to learn what the chatbot says it knows about you — and more importantly, it may inspire you to think differently about yourself today. Altogether, the interest in using AI models to find out more about ourselves and our own habits reveals how much potential they have, far beyond simply assisting with work or school assignments. Indeed, as the generative AI era approaches its 2nd year anniversary (since the November 2022 launch of ChatGPT), this question and the others like it show just how much AI has become embedded into the fabric of our lives and society, and how the more we use it, the more interesting new uses for it people find. source

The information technology sector has contributed to GDP growth in Brazil, according to official numbers released by the Brazilian Institute of Geography and Statistics (IBGE) on March 4. At 8.7 trillion Brazilian reais ($1.7 trillion), Brazil’s GDP has grown 4.6% last year compared to 2020, according to IBGE. The IT and telecommunications sector was among the best performers of the Latin economy, with 12.3% growth in 2021, contributing to a boost to the services industry overall.  This compares with agribusiness, a key sector for the Brazilian economy, which has seen a decline of 0.2% last year. According to IBGE, business activity in the information and telecommunications sector had been on the rise since start of the COVID-19 crisis. It gathered pace throughout 2021, largely driven by the need for remote work and study.  The positive performance of the IT sector in Brazil follows a growth trajectory seen in the last three years, as digital transformation within companies accelerates. When it comes to revenue, the country’s information technology sector has reached 426.9 billion reais ($76.7 billion) in 2020 — the equivalent of 5.6% of the country’s GDP. Most of it is generated in the São Paulo state, according to research. The IT and telecommunications sector in Brazil is poised to grow 8.2% in 2022, according to predictions made in February by analyst firm IDC. The research company estimates IT alone will see 10.6% growth and telecoms will see a 4% boost. “Expectations for growth in the Brazilian ICT market in 2022 are the highest for the last eight years, despite a scenario of moderate economic growth in Latin America and a period of elections in our country”, said Denis Arcieri, country manager at IDC Brazil, when the predictions were announced. According to IDC, growth in the Brazilian IT sector should be driven by device sales, while growth in the telecom will stem from mobile data sophistication, as well as the ramifications of the roll-out of 5G. Growth drivers for the enterprise IT sector will be a reflection of cloud maturity in the country, as well as an acceleration of the IT services market and a positive outlook for the software industry. Another area of growth for tech companies in Brazil is security. According to a separate study by IDC, overall security spending is expected to reach nearly $1 billion in Brazil this year, an increase of 10% in relation to 2020. Of that total, spending on security solutions will reach $860 million, the company said, with cloud security becoming a key area of focus for Brazilian IT decision-makers. source

Forrester’s Technology Strategy Impact Award seeks to recognize technology teams that have adopted high-performance technology strategies, enabling their firms to deliver on business outcomes through technology. The winner and finalists for the 2024 Technology Strategy Impact Award in APAC have built the right technology capabilities that align with their business capability needs and have done so in a highly trusted and adaptive manner. Congratulations to Macquarie’s Banking and Financial Services group (Macquarie BFS), this year’s winner, and the two finalists: Singtel and Tabcorp. Macquarie BFS: Delivering Business Outcomes With A High-Performance IT Strategy Headquartered in Sydney, Australia, Macquarie’s Banking and Financial Services group (BFS) is the retail banking and wealth management business of Macquarie Group and serves approximately 1.85 million customers in Australia, with total deposits of $A145.3 billion and a home loan portfolio of $A123.7 billion, as of June 30, 2024. Macquarie BFS is bringing the culture of technology companies to financial services and intends to keep technology at the core of everything to deliver the best digital experience to its customers and drive alignment to that business vision. Macquarie BFS’s key tenets of its high-performance technology strategy that underpins this success are: Scoring high on alignment, trust, and adaptivity. Macquarie BFS follows the tenets of “always on” and the “speed of now,” just like big tech. Its BFS control-tower approach, as well as the technology team using business objectives in their OKRs, drives strong alignment with the business. Its software development platform follows agile enterprise practices, leveraging a flexible architecture that helps them deliver business apps at high speed to drive adaptivity. Its 96% cloud adoption, following site reliability engineering (SRE) standards, drives trust inside-out. There is much more to be impressed with in terms of Macquarie BFS’s tech capabilities. Focusing on just the right style. Macquarie BFS has a strong focus on cocreation. This is extremely difficult to achieve but is what banking business typically needs. Macquarie BFS’s investment in the right tools and practices allows it to cocreate fast, but this is only possible because it has optimized investment on enabling activities, thanks to smart investments in a set of capabilities such as continuous integration and continuous delivery (CI/CD), SRE, quality, cloud, and SecOps. It also has just the right focus on amplification through its investments in AI and automation. To hear more about Macquarie BFS’s technology journey, attend Forrester’s Technology & Innovation Summit APAC, October 29 in Sydney. Presenters from Macquarie BFS will be sharing more about its technology strategy in a keynote session. Singtel: IT Becomes A Strategic Business Enabler Singtel’s story of transformation is utterly impressive. It was dealing with a legacy core, had surging business enablement demand, and was working in an overly complex organization to boot, but it was able to turn around and transition from just a connectivity provider to a trusted business-technology enabler: Singtel is experiencing improved alignment and trust. Singtel identified and prioritized initiatives in order to boost alignment between the business and IT teams. It adopted and enhanced its practices around project management, change advisory, and architecture/solution review, introducing transparent reporting to drive greater synergies. It drove adaptivity in the way it skilled, hired, and deployed the right talent flexibly across its requirements. It is enabling and amplifying business capabilities. Singtel has done extensive work in remediating tech obsolescence, improving service resiliency, and building intelligent operations and cybersecurity practices. It has also been investing in tech to improve customer experience (CX) to amplify and scale its customer-facing services through chatbots, call summarization, and post-call analysis, among other things. The better alignment between the teams has significantly improved its time to market on new initiatives such as the new iPhone launch across various markets, new eSim launch, and the launch of a B2B marketplace. As a result, Singtel has won many accolades in recognition of improved digital experience. Overall, this is a fascinating story of change in terms of the way Singtel’s consumer and enterprise businesses work closely with their technology teams while still being part of the agile squads. Tabcorp: Leading The Industry With A Data Acceleration Initiative Melbourne-based Tabcorp is Australia’s largest gambling and gaming services provider. It has more than 800,000 active customers and covers more than 4,000 venues. Tabcorp embarked upon what it calls a data acceleration initiative in early 2024 to enable omnichannel, connected CX, and real-time business insights powered by data as a service. Tabcorp’s main focus areas in this regard were as follows: Driving trust and resilience. This data initiative centers around creating a single view of customers, building AI-led personalization at scale, and using a resilient architecture to build trust across customers, the business, and external partners. In the process, it simplified the architecture and significantly reduced legacy reporting, driving down the total cost of ownership. Business and IT worked together to identify the metrics that matter and built pipelines from trusted sources of data into an information model that it co-created with the business. Amplifying business outcomes. Tabcorp’s data acceleration initiative is a wonderful example of how the right application of data, AI, and personalization at scale can amplify your business outcomes. Tabcorp is powering several use cases around personalization, recommendation, the next best action, discovery, campaigns, and conversations. On the other side, this initiative is driving Tabcorp to build a highly resilient, automated, and efficient infrastructure to enable scale. These lessons, combined with other initiatives, are leading to an all-around improvement in IT performance. There is so much more to talk about in terms of how Tabcorp is building a highly adaptive IT organization running on agile practices, leveraging a strong enterprise architecture framework that allows it to reorient itself to new priorities swiftly and deliver to business outcomes. The announcement of our APAC winner and finalists concludes Forrester’s Technology Strategy Impact (TSI) Awards for this year. But you can learn more about their winning secrets by attending Forrester’s Technology & Innovation Summit APAC, taking place in Sydney and digitally, October 29, 2024. We look forward to

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Strella, a startup using artificial intelligence to automate and accelerate customer research, announced today that it has raised $4 million in seed funding led by Decibel, with participation from Unusual Ventures. The company’s AI-powered platform aims to deliver human insights up to 10 times faster and at half the cost of traditional research methods. Founded by Lydia Hylton and Priya Krishnan, Strella is tackling a long-standing challenge in market research: the trade-off between speed and depth of customer insights. The company’s AI moderator can conduct interviews, analyze responses, and synthesize findings in real-time, dramatically condensing timelines for gathering qualitative feedback. Strella’s AI-powered interview platform prepares to connect with a participant for a study on online grocery shopping habits. The interface showcases the blend of technology and human interaction that defines the company’s approach to market research. (Credit: Strella) AI interviews: The future of scalable qualitative research “Traditionally, if you wanted any scale in a customer research project, you had to run surveys. It’s way too painful to do human-led interviews if you want to have 30, 40, 50 interviews on a topic,” said Lydia Hylton, Co-Founder and CEO of Strella, in an interview with VentureBeat. “We’re now able to get the richness of qualitative feedback that you get from a conversation, but at the scale of a survey and at the speed of a survey.” The platform is designed to work alongside human researchers, allowing companies to blend AI-moderated and human-led interviews within the same system. This flexibility addresses concerns about losing the human touch in customer interactions. “We’ve designed our platform to be conducive to human-centered research as well,” explained Priya Krishnan, Co-Founder of Strella. “Let’s say you want to run a research project and you want to interview 10 of your customers, we give you the flexibility to choose to use the AI moderator as much or as little as you want.” Strella’s AI-powered interview platform showing a customizable questionnaire for online grocery shopping habits. The interface allows researchers to easily add questions, tasks, and media elements to gather comprehensive customer insights. (Credit: Strella) Enhancing customer feedback: Strella’s approach Strella’s method could significantly alter how companies gather customer feedback and inform product decisions. By lowering the time and cost barriers to qualitative research, the platform may enable more frequent and comprehensive customer engagement across various industries. The company reports it has already signed on 15 customers, including notable names like Duolingo and Spanx. This early traction in both the tech and consumer goods sectors suggests broad applicability for Strella’s technology. Jessica Leao, partner at Decibel, highlighted the potential impact of Strella’s technology: “You get to transform this entire world of quantitative research into qualitative research, because you’re no longer blocked on time. You’re no longer blocked on scheduling.” However, Strella enters a competitive field. Established players like Qualtrics dominate in quantitative research, while numerous startups are leveraging AI for various aspects of market research. Strella’s differentiation lies in its end-to-end automation of the qualitative research process, from interview moderation to insight synthesis. The AI-driven future of market research: Opportunities and challenges The funding round comes at a time of growing interest in AI applications for business intelligence. As companies seek to become more data-driven and customer-centric, tools that can rapidly deliver actionable insights are increasingly valuable. Looking ahead, Strella aims to expand its reach across industries and company sizes. “We really want customer research to be accessible for teams of all sizes, across industries,” Krishnan said. “Up until now, research has really only been something that medium to larger companies have had the resources to do.” As Strella emerges from stealth mode with this funding announcement, it faces a twofold challenge: proving its AI can consistently deliver high-quality insights across diverse research scenarios, and convincing businesses to shift away from established research methodologies. The company’s success hinges not just on technological prowess, but on its ability to change deeply ingrained corporate habits around customer feedback. If Strella can overcome these hurdles, it may usher in a new era where AI-driven qualitative research becomes as commonplace as surveys are today. In a business world increasingly driven by data, Strella’s approach could be the difference between companies that truly understand their customers and those that are left guessing. source

Climate Week From September 22-29, New York City hosts Climate Week, an annual event that brings together global leaders, policymakers, businesses, and civil society to tackle the pressing challenges of climate change. The week features a series of conferences, workshops, and exhibitions to promote sustainable practices, address climate justice, encourage international cooperation, and raise public awareness. Each year, we are reminded that the past 12 months have marked yet another “Top 10” high for global temperatures, emphasizing the urgent need for action—though the pace of change remains frustratingly slow. The Data Center Dilemma The data center industry has come under increasing scrutiny for its environmental impacts and rapid growth, driven partly by AI technologies’ energy demands. For example, in its sustainability report released in May, Microsoft said its emissions grew by 29% since 2020 due to the construction of more data centers designed and optimized to support AI workloads.  Likewise, Google reported increased electricity demand driven by artificial intelligence, and its growing fleet of data centers has caused the company’s greenhouse gas emissions to grow by 48% above its 2019 baseline, creating a challenge for the tech giant in meeting its carbon neutrality goals by 2030. These companies should be applauded for their transparency and courage to tell the facts as they are.  It demonstrates leadership, promotes learning and improvement, encourages industry standards, and, most importantly, highlights the problem. This ever-increasing facility growth and electricity consumption poses a significant struggle as data centers strive to balance the need for increased computational power with the imperative to minimize their environmental footprint. IDC calculates worldwide data center energy consumption for 2023 to be 352TWh and projects a 19.5% CAGR, growing to 857TWh by 2028. While harder to quantify due to of a lack of standards and available information, scope 3 emissions from constructing and outfitting data centers with IT equipment also contributes to industry emission growth.   Why Aren’t We Seeing More Progress?                                While AI garners most market attention, when surveyed, datacenter operators indicated that improved environmental sustainability was their second-highest initiative, ahead of AI, but behind business and financial management. So, if the data center operators know and prioritize the problem, why isn’t more progress being made? Like most complex problems, there are a multitude of factors that contribute to it.  Demand – The first is the demand for digital services.   As enterprises pursue digital transformation and invest in artificial intelligence to create unique value, the demand for data centers and the associated electricity consumption is rising substantially.  Organizations are unwilling to sacrifice operational improvements and gains they expect from these efforts to meet sustainability goals.   Global political cooperation and policy. It will take a combination of political agreements, like the Paris Agreement, and stricter local regulations on emissions to drive the change in behavior and investment in renewable energy infrastructure. Transition to Renewable Energy. As governments and businesses set ambitious targets to reduce carbon emissions, the demand for renewable energy is outpacing supply, and globally, electric demand is outpacing new generation supply.  Many electricity grids were built for centralized, fossil-fuel-based power generation and are not yet fully optimized to handle the decentralized and intermittent nature of renewable sources like wind and solar. Taking Immediate Steps on Energy Efficiency The phrase “Think globally, act locally” has been part of our collective consciousness since the 1970s, resonating across various societal challenges due to its timeless relevance. Today, this principle particularly applies to datacenter operations. While most datacenter operators may not have the influence to shape global policies or invest directly in large-scale renewable energy initiatives, they can drive change by focusing on energy efficiency at a local level to reduce demand. While some companies or individual executives prioritize sustainability metrics, viewing environmental responsibility as a critical driver of their decisions, others see these efforts as secondary or “soft” benefits. For this latter group, decision-making is anchored in hard financial metrics, focusing on return on investment (ROI). Energy efficiency initiatives appeal to both types and are aligned with top datacenter priorities. Electricity costs account for the most significant portion of data center facility operating expenses—ranging from 45% to 60%—depending on location and data center type.  Simultaneously, growth in industrialization and electrification have led to higher electricity demand, outpacing generation, which is expected to cause electricity prices to increase. The combination of rising electricity prices and increased electricity consumption is poised to make data centers significantly more expensive to operate. To assist organizations in understanding the potential impact, IDC published The Financial Impact of Increased Consumption and Rising Electricity Rates in Data Center Facilities.  The research includes scenario planning for a 1 MW data center in the United States, Germany, and Japan.   IDC projects that a typical 1 Megawatt data center consumed 6.6 Gigawatt hours (GWh) of electricity in 2023 and will grow to between 13 to 16 GWh by 2028 through capacity expansion, increased utilization, and higher density deployments. Simultaneously, IDC expects energy costs to continue to grow above historical levels.  The percentage growth in electricity spend will exceed a CAGR of 15% in all cases, with most scenarios showing growth of over 20%. When measured in absolute spending increase, it is expected to near or exceed $1,000,000 annually. While the model assumes energy efficiency improvements, an organization can expect to save between $500K and $1,900K with energy efficiency improvements that are 10% greater than the industry average. Conclusion Prioritizing energy efficiency in data centers is no longer just a matter of environmental responsibility—it’s essential for sound datacenter financial management. As the demand for digital services, AI, and cloud computing continues to soar, the pressure on organizations to minimize their carbon footprint while managing rising electricity costs will only intensify. By taking action now—investing in more energy-efficient technologies and optimizing operations- organizations can reduce their environmental impact and significantly cut operating expenses, their top two priorities. The financial and environmental stakes are clear, and the time to act is now. Energy-efficient data centers are essential for the future of business and the planet. source