As organizations navigate the challenges of technology adoption across generational lines, organizations are increasingly focusing on strategies to bridge the gap between tech-savvy younger employees and older workers with varied levels of proficiency.  Contrary to stereotypes, older employees often possess a wealth of tech experience from earlier computing eras, such as troubleshooting first-generation PCs or early networking systems.  Graham Glass, founder and CEO of Cypher Learning, says assessing the “technology history” of all employees can provide valuable insights into their skills and comfort levels.  “By treating training needs as individual as a medical history, organizations can design programs that respect experience while addressing gaps, avoiding one-size-fits-all approaches that may alienate staff,” he says.   He adds that equally as important as generational differences are cultural and ethnic differences.  “When you’re driving more tech proficiency in the workplace, consider every user’s point of view,” Glass says.   Ryan Downing, vice president and CIO of enterprise business solutions at Principal Financial Group, points to cloud transformation as a prime example of generational collaboration, with engineers across age groups elevating their skills together.  Related:Tech Company Layoffs: The COVID Tech Bubble Bursts “What I find most impressive is how newer employees bring fresh perspectives and energy, while more experienced team members contribute wisdom and expertise,” he says. “This dynamic levels the playing field, strengthens team cohesion, and ensures every voice is heard.”  Cross-Generational AI Adoption  To foster inclusive AI adoption, Downing says organizations should shift the conversation from merely adopting new tools to transforming ways of working.  “At Principal, we are beginning to pilot coaching programs that focus on setting clear outcomes that can help teams improve efficiency and quality,” Downing explains.  The programs guide teams to explore how AI tools can drive value creation in ways that differ from traditional approaches.  “This outcome-driven mindset encourages exploration and reduces apprehension around AI tools,” he says.   Tailored training is also playing in bridging the generational tech gap. Downing says at Principal, training is balanced with a mix of formal learning opportunities, coaching and mentoring, and meaningful assignments.  “This approach allows team members to apply new skills in real-world scenarios,” Downing says. “By offering varied learning methods, we can accommodate different working styles and readiness levels, ensuring all team members can effectively engage with new technologies.”  Related:Risk Management for the IT Supply Chain Downing explains the primary challenge typically isn’t a lack of tools or willingness to learn, but rather the tendency to treat AI tools as mere add-ons rather than enablers of transformation.  “It’s so important not to underestimate the human element of implementing these new tools to help team members reimagine their workflows,” Downing says. “Emphasizing transformation over tools helps to ensure meaningful adoption across these generational lines.”  Glass explains that while younger workers may adapt quickly to AI tools, older employees often need reassurance about their role in the workplace and the utility of AI as a tool to enhance, not replace, their contributions.  “Personalized learning platforms powered by AI allow employees to learn at their own pace, ensuring proficiency without wasting time or risking embarrassment,” he says.  Peer-to-peer mentoring and collaboration further bridge the gap, allowing younger workers to share their digital fluency while benefiting from the problem-solving resilience of older colleagues.  “The less exposed to AI people are, the more qualms they have,” Glass says. “Our recent research shows younger men are less worried about AI than, say, older workers or women.”  Related:The Top Habits of High-Performing IT Development Teams That “comfort gap” is a function of time spent experimenting with the technology, or lack thereof, so it’s a good idea for businesses to encourage it.  “Two more big issues that recur are privacy and fear of AI taking over peoples’ jobs,” Glass adds.  Managers can address the first by framing house rules governing AI use — defining tasks it shouldn’t be exposed to, for example. As for the second — reassure employees, especially older ones, that AI is a tool meant to take rote chores off their plates and elevate their roles.  “The more you underline how essential your people are, the less they’re apt to fret about job security,” Glass says.   Measuring Success  Organizations implementing multigenerational technology training programs often measure success through a combination of immediate feedback and long-term metrics, Gartner analyst Autumn Stanish explains.  “Retention and attraction rates are key indicators, such as tracking whether employees are staying longer or if the company is drawing new talent due to its reputation for inclusivity,” she says.   Stanish points to Broadridge’s reverse mentoring program, where younger employees mentored older colleagues on work-related topics.  After the program, both mentors and mentees completed surveys using a 10-point scale to evaluate outcomes like increased belonging, broadened perspectives, and willingness to recommend the experience.  Stanish says short-term insights from surveys help guide improvements, while broader goals, such as enhanced employee satisfaction and retention, require time to fully materialize.   Combining these methods allows organizations to fine-tune their programs and foster inclusivity effectively.  “The little surveys and moments where we gather feedback help us connect with employees directly, and over time, those qualitative insights drive the bigger quantitative outcomes,” she says.  source

QuickBooks Payroll is a popular pay processing software thanks to its full-service payroll, well-rounded features, and fast syncing with the QuickBooks accounting system. However, it has limited HR tools and can be pricey to use, depending on the plan you get. If you’re looking for a QuickBooks Payroll alternative that costs less, handles global employee payments, or offers more HR features, here are some options you can consider. 1 Paycor Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Micro (0-49 Employees), Small (50-249 Employees), Medium (250-999 Employees) Micro, Small, Medium Features API, Check Printing, Document Management / Sharing, and more 2 Deel Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features 24/7 Customer Support, API, Document Management / Sharing, and more 3 Velocity Global Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Employee Database, Multi-Country Payroll, Onboarding, and more Top QuickBooks Payroll alternatives comparison These alternatives to QuickBooks Payroll, including QuickBooks, offer tax reporting and filing assistance, automatic pay computations, benefits administration, and essential tools to manage employee information. Starting monthly price Separate contractor plan (per month) This is a separate contractor payments plan, and is best for those that only need to pay contract workers. Global payroll tools Time tracking QuickBooks Payroll $50 base fee + $6 per employee $15 for up to 20 workers + $2 per additional worker No Included in higher tiers Gusto $40 base fee + $6 per employee $35 base fee + $6 per worker Yes Included in higher tiers OnPay $40 base fee + $6 per employee No No Via integrations Square Payroll $35 base fee + $6 per employee $6 per worker No Yes Paychex Flex Custom No No Paid add-on RUN Powered by ADP Custom No Yes Paid add-on Gusto: Best overall Image: Gusto As a payroll software, Gusto has many of the same perks as QuickBooks, such as automatic salary and tax computations, wage garnishments, and automated tax filings. However, it has a broader range of HR features to streamline the employee lifecycle. It can post jobs, onboard workers, track attendance, plan work shifts, and monitor performance reviews. Gusto can also pay international contractors in over 120 countries. And with its employer of record (EOR) service, Gusto Global, it can compliantly hire and pay workers in Australia, Brazil, Canada, Germany, India, Ireland, Mexico, the Netherlands, the Philippines, Portugal, the United Kingdom, and Spain (as of this writing). Pricing QuickBooks Payroll and Gusto offer three plans, but Gusto’s starter tier is slightly cheaper. It only costs $40 plus $6 per employee monthly, whereas QuickBooks Payroll’s starter plan is priced at $50 plus $6 per employee monthly. Plus, Gusto’s starter tier has more HR features, such as basic paid time off (PTO) policies, custom offer letter templates, and onboarding checklists. Here are its pricing plans: Simple: $40 base fee per month plus $6 per employee per month. Plus: $80 base fee per month plus $12 per employee per month. Premium: $180 base fee per month plus $22 per employee per month. It also offers a contractor plan if you only pay contract workers. Contractor only: $35 base fee per month plus $6 per worker monthly. While Gusto’s contractor plan isn’t as affordable as QuickBooks Payroll’s ($15 monthly for up to 20 workers plus $2 per additional worker), Gusto includes new hire reporting in its package. This can save you time, especially if your business is located in California or a state that requires companies to report newly hired contract workers. Gusto pros and cons Pros Cons HR features are more comprehensive than QuickBooks Payroll Offers EOR services and global contractor payment tools Its payroll platform is more intuitive and user-friendly than QuickBooks. Its tarter tier only comes with single-state pay runs. Time tracking, multi-state payroll, expense claims, applicant tracking, and advanced HR tools are included in higher tiers No mobile app When to choose Gusto over QuickBooks Payroll Gusto is my top QuickBooks Payroll alternative mainly because of its feature-rich platform. It’s great if you want a payroll system that can manage hiring to onboarding tasks with ease. QuickBooks doesn’t have an applicant tracking system (ATS) to monitor candidates, and its onboarding features aren’t as extensive. With Gusto, you can track applicants, create virtual welcome cards for new hires, manage email and software access, and run background checks via Checkr directly from its platform. When it comes to payroll taxes and tax filings, both will calculate federal, state, and local taxes, but only Gusto includes tax payment and filing assistance across all levels in its starter tier. With QuickBooks, you must upgrade to at least its Premium plan to get automated local tax filing services. Gusto’s functionalities also extend beyond just processing US and global payroll. It can help with state tax registration and offers an R&D tax credit service that lets you save up to $250,000 in payroll taxes each year. So, between features and pricing, I consider Gusto the top alternative to QuickBooks Payroll for most small businesses. The Gusto payroll dashboard allows you to run payroll, start off-cycle payments, and view pay processing tasks. Image: Gusto Learn more about Gusto OnPay: Best value for money Image: OnPay What sets OnPay apart from QuickBooks Payroll and the others on my list is its flat-rate pricing. You only get one plan, with all its features and services included in that package. So, you never have to worry about whether or not a specific functionality will cost you extra or require a plan upgrade. OnPay’s simple pricing also gives you plenty of bang for your buck. For a monthly fee of $40 plus $6 per employee, you get full-service payroll, access to benefits plans, employee self-service tools, and essential HR and team management features. As an added perk, OnPay provides white-glove setup and data migration support to get you started

hide.me VPN fast facts Our rating: 4.1 stars out of 5Pricing: Starts at $4.57/mo (annual plan)Key features: Generous free version. 10 simultaneous device connections. Affordable subscription options. hide.me VPN is a Malaysian-based VPN service, offering a generous free version with unlimited data and affordable premium plans. It’s available on Windows, macOS, Linux, Chrome, Android, and iOS, to name a few. While hide.me can be a good choice for users on a budget, it may not be the best for users needing an extensive server network. Its server fleet only has around 2,600 servers across 91 locations, compared to other VPNs in 2025 that usually provide 3,000+ servers and a larger selection of locations. Continue reading to explore hide.me VPN’s, pricing, features, and performance based on our hands-on review. Semperis Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Small (50-249 Employees), Medium (250-999 Employees), Large (1,000-4,999 Employees), Enterprise (5,000+ Employees) Small, Medium, Large, Enterprise Features Advanced Attacks Detection, Advanced Automation, Anywhere Recovery, and more ESET PROTECT Advanced Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Advanced Threat Defense, Full Disk Encryption , Modern Endpoint Protection, and more NordLayer Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Small (50-249 Employees), Medium (250-999 Employees), Large (1,000-4,999 Employees), Enterprise (5,000+ Employees) Small, Medium, Large, Enterprise hide.me VPN pricing In 2025, hide.me has a monthly, a yearly, and a 26-month premium plan. It also has a dedicated free version, with no credit card required. Across the board, hide.me offers very affordable pricing for its premium plans. In particular, its one year plan at $4.57 per month is a good price compared to other VPN providers, with annual plans from other VPNs averaging around $4 to $7. Duration Price 1 month $9.95 per month 1 year $4.57 per month 26 months $2.69 per month When I first reviewed hide.me in 2023, it did not have a one-year plan available. The closest thing to it was a six-month subscription at $5.82 at the time. In 2025, I’m happy to report that a one year subscription is now being offered at $4.75 per month — a reasonable price when put side by side with other one year subscriptions like NordVPN Basic for $4.99 per month and ExpressVPN’s $6.67 annual subscription. hide.me VPN continues to have their longer 26-month subscription at $2.69, which is a good pick for long-term hide.me users that want a lower monthly fee. hide.me’s monthly subscription priced at $9.95 is also well-below industry average, as other VPN providers charge around $10-17 for a monthly plan. Fortunately, all three hide.me premium tiers come with a consumer-friendly 30-day money-back guarantee. Before making a decision, I highly recommend using hide.me’s free version or purchasing the one year subscription and using the 30-day money-back guarantee if you’re not satisfied. hide.me free version hide.me offers a full version of its VPN for free. While most free VPNs have a monthly data cap, hide.me’s free version offers unlimited data to its users and possesses the same security protocols and encryption as the premium version. hide.me VPN’s free version on desktop. Image: Luis Millares I personally appreciate how hide.me VPN’s free version doesn’t require any credit card or payment information to access. This allows it to be a fully free, no-strings-attached free plan that doesn’t require users to hand over unnecessary data. However, there are limitations. The free version doesn’t have hide.me VPN’s Smart Guard ad, tracker, and malicious websites blocker and it only allows for one connection and access to seven locations compared to the 10 connections and 91 locations available with the premium plan. The seven available server locations are France, Finland, Netherlands, Switzerland, the United Kingdom, and the United States. Two years ago, hide.me VPN’s free plan didn’t allow you to select which free server you connected to and simply chose one automatically. Now, their free plan finally lets users connect to their preferred connection, among the seven free country servers provided. While these are sizable limitations, having unlimited data on a free version is still a huge advantage. hide.me VPN pros Free version with unlimited data. 10 simultaneous device connections. Very affordable pricing. Customizable app experience. Company has a clean privacy reputation. hide.me VPN cons 2,600 server network is lower than average. Free version offers slow speeds. Desktop app looks dated. Security: Is hide.me VPN safe? hide.me comes with the requisite security protocols we want in a modern VPN. It has OpenVPN, WireGuard, IKEv2 IPsec, and even SSTP and SoftEther. hide.me also includes AES-256 encryption, a built-in kill switch, and DNS leak protection. hide me has a no-logs policy, which states that they don’t collect personal data or monitor or log browsing behavior from its users. The VPN provider also states that all its usage data is completely anonymous. Back in 2023, hide.me VPN’s most recent independent audit was one conducted by Defense Code Ltd. in 2015. In 2025, hide.me VPN finally has a more recent third-party assessment done by Securitum,  published in July 2024. To me, this is a significant development considering how important it is for VPN audits to be recent and timely — considering how things can change quickly in terms of the security of an application like a VPN. In the Securitum audit, the firm confirmed that hide.me VPN did, in fact, apply its no-logs policy properly and did not have any issues that could compromise overall user privacy. hide.me also continues to provide a publicly accessible Transparency Report (2023) that covers illegal activity usage, copyright data, and law enforcement requests received by the VPN. This shows that hide.me is committed to upholding transparency and trust with its users. hide.me is based in Malaysia and isn’t obligated to store logs by local laws — a plus for privacy enthusiasts concerned about government surveillance. With its release of a more up-to-date third-party audit, hide.me hits all the marks needed to

Threat actors love phishing because it works. It is particularly effective in cloud infrastructure — once they’re inside, they gain access to anything else related to that cloud. According to Hornetsecurity’s Cybersecurity Report 2025, there were more than 471 million emails sent in 2024 that were flagged as “malicious.” In terms of email attacks, phishing remained the top attack method at 33.3%. This makes it by far the most common attack vector, next to malicious URLs. But not all phishing is the same. Highly targeted phishing campaigns against specific individuals or types of individuals are known as spear phishing. It’s important to be able to spot phishing in general. But for targets of spear phishing, it is even more essential to spot the telltale signs, as the damage done in these attacks tends to be greater. Semperis Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Small (50-249 Employees), Medium (250-999 Employees), Large (1,000-4,999 Employees), Enterprise (5,000+ Employees) Small, Medium, Large, Enterprise Features Advanced Attacks Detection, Advanced Automation, Anywhere Recovery, and more ESET PROTECT Advanced Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Advanced Threat Defense, Full Disk Encryption , Modern Endpoint Protection, and more NordLayer Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Small (50-249 Employees), Medium (250-999 Employees), Large (1,000-4,999 Employees), Enterprise (5,000+ Employees) Small, Medium, Large, Enterprise What is phishing? Phishing is basically an online version of fishing — except instead of marine life, the goal is to lure gullible users to reveal passwords and personal information by clicking on a malicious link or opening an attachment. Typical attacks are sent through email. Sometimes, cybercriminals pose as representatives of cloud service providers and send messages related to a variety of online services and applications. Phishing messages are often skillfully written. A common tactic is to impersonate reputable brands like Facebook and Microsoft, as well as banks, internet service providers, the IRS, and law enforcement agencies. These emails contain the appropriate logos to appear legitimate. Anyone following their directions and handing over their login details or clicking on a link is likely to infect their device, download malware, or be locked out of their network and asked to pay a ransom. Phishing email example. Image: TechRepublic Once inside an application running in the cloud, threat actors can expand their attacks across more accounts and services. For example, breaching an organization’s Google or Microsoft cloud gives the attacker access to email accounts, contact lists, and document creation. By targeting a phishing campaign to obtain cloud credentials, the bad guys have a better chance of attracting a larger payload. How can you identify a phishing email or message? While phishing attempts can seem authentic, there are telltale signs which indicate that a message is part of a phishing attack. Here are a few to watch out for: Typographical or spelling errors. Unusual use of symbols or punctuation. Content is incoherent or poorly written. Message or email came from an unknown recipient. Uses generic greetings such as “Dear customer” or “Dear User.” Usually talks about something that’s too good to be true. Has suspicious links or file attachments. What is spear phishing? While phishing is generalized in that one phishing email may be sent to millions of people, spear phishing is highly targeted. The goal is to compromise the credentials of a specific person, such as the CEO or CFO of a company, as we reported on in 2023. In spear phishing, the messaging is carefully crafted. Criminals study social media postings and profiles to obtain as much data as possible on a victim. They may even gain access to the person’s email and remain invisible for months while they evaluate the kind of traffic the person has coming in. Spear phishing messages are designed to be far more believable than generic phishing attempts, as they are based on data taken from the person’s life and work. Reconnaissance makes the phishing email, text, or call very personalized. Spear phishing email example. Image: TechRepublic In the cloud, a high-value target might be someone with administrative privileges for systems spanning thousands of individual accounts. By compromising that one identity, hackers have free rein to infect thousands more users. SEE: Securing Linux Policy (TechRepublic Premium) What is the main difference between phishing and spear phishing? What distinguishes spear phishing from regular phishing is that the message generally has much more detail and adopts a tone of familiarity. The level of surprise and urgency is generally ramped up in spear phishing and often involves transferring money. Phishing Spear Phishing Target Mass or large group of people Individual or group with authority (CEO, CFOs, IT admins) Message’s level of detail Low-to-medium Very high Tone of message Generic or general Portrays familiarity with target; personalized Time frame Done in one instance Done over a long period of time Depth of research required Low Very high Method/medium Text, call, online message, or email Commonly done via business emails End goal Stealing a user’s credentials or obtaining small amounts of money from victim Typically involves transferring large sums of money or confidential data To be clear, many of the red flags for potential phishing emails also apply to spear phishing. They include typos in the text, bad grammar, emails from unknown recipients, suspicious links, a false sense of urgency, or requests via email to enter confidential information. Phishing emails go to large quantities of people rather than to specific individuals. For example, an email might be sent to thousands of people or everyone in one company telling them that IT wants them to verify their credentials by clicking on a link and entering them on a form. Spear phishing is more specific. For example, a CEO’s assistant might be targeted by a criminal who impersonates an email from the CEO. The hacker has been monitoring email messages and social media for months and knows

Most of us share and store huge amounts of personal data online, from our names and addresses to photos of our loved ones. In many ways, firms like Apple, Google, and Meta are the gatekeepers of this sensitive information. But what happens when the authorities come knocking? It appears that Silicon Valley often rolls over and complies.  Over the last 10 years, Apple, Google, and Meta have handed over data on 3.1 million accounts to the US government, according to a new report by Swiss software company Proton.  The number of times officials have requested user data from Big Tech has skyrocketed by an average of 600% over the same timeframe, Proton found. Meta’s data sharing surged by 675%, marking the largest increase, followed by Apple at 621% and Google at 530%. Apple, Google, and Meta comply with between 80-90% of US government data requests, according to Proton. This potentially includes handing over user emails, files, messages, and other highly personal information.  TNW Conference – Groups get the best fun and the best deals Bring your team and multiply your efficiency to cover more grounds and collect new leads. While data requests also saw an uptick from countries including Germany, France, and the UK, the US took the lion’s share. “All that’s required for the government to find out just about everything it could ever need is a request message to Big Tech in California,” said Raphael Auphan, COO of Proton. “And as long as Big Tech refuses to implement widespread end-to-end encryption, these massive, private data reserves will remain open to abuse.” Data sharing with US authorities has surged since 2014. Credit: Proton Government desires for data Proton — best known for its products ProtonMail, ProtonVPN, and ProtonDrive — has long positioned itself as a privacy-first alternative to Big Tech firms. However, the company also complies with its fair share of government requests for user data.  According to Proton’s own transparency report, it received 13 data requests from Swiss authorities back in 2017, soaring to 6,378 by 2024. Of those, it complied with 5,971 of the requests. That’s 93% — higher than the Big Tech companies highlighted in the new report.  However, unlike Silicon Valley’s giants, Proton encrypts emails, files, and VPN traffic in a way that even the company itself cannot read or access. So, even if authorities demand data, there’s very little it can provide.   “In no circumstances can we share emails, files, contact lists, calendar entries or other personal content,” a Proton spokesperson told TNW. “We cannot share what we do not have.” Moreover, Proton operates under strict Swiss privacy laws, which means foreign governments cannot request data from it without first going through Swiss courts, adding an extra layer of security for users.  But under specific circumstances, the company can hand over metadata about the account, including IP address, email address, and recipient emails. “Proton is dedicated to protecting user privacy but that does not mean it’s a safe haven for illegal activity,” the spokesperson said. “Proton is subject to national laws and has legal obligations, to which we are obliged to comply unless we have legal grounds to contest, which does not happen very often in Switzerland.”   source

When I talk to B2B leaders about their generative AI (genAI) adoption efforts, I hear a mix of frustration, FOMO, and skepticism. Many feel stuck. They’re unsure whether their organization is behind, and they suspect other leaders have cracked the code. They also field tough questions about the ROI of adoption efforts. But the conversation quickly shifts when they ask the most impactful questions: “What can we do with where we are today? Are there practical steps we can take now to turn possibility into reality — or even a quick win?” These are the right questions to ask because they shift the conversation from uncertainty to action. Instead of dwelling on what’s missing or feeling behind, leaders start focusing on what’s within their control. That’s where real progress begins and things get exciting. When the focus turns to practical options, the conversations become energizing, opening the door to tangible steps that drive impact. During my keynote presentation at our upcoming B2B Summit North America, I’ll explore how leaders can turn genAI possibilities into reality by tackling the fundamental challenges that still hold them back. These challenges, once addressed, not only help organizations achieve value today but also help them adapt to whatever genAI advancements come next. Fix The Engine Before Your Competitors Do GenAI can’t deliver real business value if a foundation is broken. Too many B2B organizations are trying to layer genAI on top of scattered, siloed, and outdated technologies, data, and processes. As a result, they can’t connect the right insights, automations stall, and teams are unsure of how to apply genAI beyond basic tasks. The B2B organizations that move ahead will be the ones that fix their engine — creating the right mix of technology, data, and processes — before their competitors do. Close The AI Literacy Gap To Unlock Real Impact When I speak to leaders, they often assume that their teams will know how to apply genAI to their work, but the reality is very different. Without AI literacy, employees hesitate, unsure of where genAI adds value or questioning whether they’re “doing it right.” As one senior AI operations leader at a leading B2B technology company put it, “Whatever communication, enablement, or change management efforts you think you’ll need, plan on tripling them.” Organizations that succeed with genAI don’t just introduce new tools. They over-communicate, over-enable, and over-invest in change management to ensure that teams have the confidence, skills, and context to integrate genAI into their daily workflows. Prioritize ongoing training and learning opportunities with hands-on experimentation and clear guidelines to accelerate adoption and move beyond surface-level efficiency gains for transformation. Make Collaboration Your GenAI Advantage The majority of genAI success stories that I hear aren’t from isolated teams. They’re happening where marketing, sales, product, customer success, IT, and legal teams are collaborating with shared data, shared goals, and a clear genAI strategy. These teams also work closely with their vendors, agencies, tech providers, and partner ecosystem so that they can move faster and do the right things together. Leaders who foster alignment, break down silos, and create a culture of AI-driven innovation across their ecosystem are the best positioned to win. Choose Progress Over Perfection The leaders who see real results with genAI aren’t waiting for perfect conditions. They’re fixing what’s in their control today. The good news? You don’t have to figure it out all alone. At B2B Summit North America, I’ll be diving deeper into these challenges and sharing practical strategies to help your organization move forward without getting lost in the hype. Join me in Phoenix, March 31 to April 3, and let’s talk about what’s really working, what’s not, and what you can do right now to stay ahead. source

The religious composition of the United States has been fairly stable in half a dozen Pew Research Center surveys conducted since 2020. The Christian share of the adult population has been between 60% and 64% in these surveys, while the religiously unaffiliated share has ranged from 28% to 31%. Adherents of religions other than Christianity have consistently accounted for 6% or 7% of U.S. adults throughout this period. Over the longer term, however, Christians have been declining as a percentage of the U.S. adult population, while the share that is religiously unaffiliated has been rising. (For an extended discussion of what explains the short-term stability in American religion amid a longer-term decline, refer to this report’s Overview.) This chapter draws on the 2007, 2014 and 2023-24 Religious Landscape Studies to summarize the long-term trends in Americans’ religious identities. The data shows that the Christian share of the population has declined across many demographic groups. Compared with 2007, the percentage of people who describe themselves as Christians is lower among men and women; college graduates and those with less education; all racial and ethnic groups large enough to analyze; all age groups; and all geographic sectors of the country. The picture is reversed for the religiously unaffiliated – a group sometimes referred to as religious “nones.” The “nones” are made up of U.S. adults who describe themselves as atheists, agnostics or “nothing in particular” when asked about their religion. The ranks of “nones” have grown among men and women, married and unmarried people; college graduates and people with less education; all large racial and ethnic groups; all age groups; and in all regions of the country. This chapter includes sections on: The chapter concludes with a set of detailed tables on the religious composition of key demographic groups. Trends within Christianity In the 2023-24 Religious Landscape Study (RLS), 62% of respondents identify as Christian, which is lower than the Christian shares measured in the 2007 (78%) and 2014 (71%) studies. The Protestant share of the population declined from 51% in 2007 to 40% in 2023-24. The Catholic share of the population, meanwhile, ticked down from 24% in 2007 to 21% in 2014. Since then, it has ranged between 18% and 21% in Center surveys, and it stands at 19% in the 2023-24 RLS. Members of the Church of Jesus Christ of Latter-day Saints (widely known as Mormons) have accounted for 2% of respondents in all three religious landscape surveys. Orthodox Christians account for 1% of the population in the latest RLS. Fewer than 1% of respondents in the new survey identify as Jehovah’s Witnesses, and 1% identify either with more than one Christian group (e.g., people who say they identify as both Protestant and Catholic) or with a variety of other, smaller Christian groups (including Messianic Jews, Christian Scientists, or offshoots of Catholicism that are not in communion with Rome). Christian shares across social and demographic groups In all three of our landscape studies, younger Americans, men, unmarried people and college graduates have identified as Christians at lower rates than, respectively, older adults, women, married people and adults with less than a college degree. But one thing all these demographic groups have in common is a long-term decline in the share who identify as Christians. For example, although women have identified as Christians at higher levels than men in all three landscape surveys, the share of women saying they are Christian has dropped from 82% in the first RLS (2007) to 66% in the most recent one (2023-24). In addition, people of every racial and ethnic background that we measure are less likely to say they are Christian now than they were in 2007, as are people in every major region of the U.S. A detailed look at the size of Protestant denominations One feature of the RLS is that it includes detailed, branching questions to gather information about specific types of Protestants.   The RLS seeks to learn not just whether someone is Protestant, but also what family of denominations (Baptist, Methodist, Lutheran, etc.) they may belong to. In addition, the RLS goes a step further, seeking to learn which specific denomination within a Protestant family the respondent identifies with, if any. We ask Baptists, for instance, whether they identify with the Southern Baptist Convention; the American Baptist Churches USA; the National Baptist Convention, USA; or another Baptist church. We ask Methodists whether they identify with the United Methodist Church, the African Methodist Episcopal Church, the Global Methodist Church, or another kind of church. We take this information about which specific denomination respondents identify with and then we categorize Protestants into one of three major Protestant traditions – the evangelical tradition, the mainline tradition or the historically Black Protestant tradition. These divisions within Protestantism are important, because each has a distinctive combination of beliefs, practices and histories. Still, some respondents don’t identify with any specific denomination. For example, some describe themselves as “just Baptist,” “just Lutheran” or “just Christian” without providing additional details. In these cases, we use a question that asks respondents whether they think of themselves as “born-again or evangelical” Christians, along with information about their race and ethnicity, to help classify them into one of the three major Protestant traditions. (Refer to Appendix B for complete details about how Protestants are sorted into the evangelical, mainline and historically Black traditions.) All three of these Protestant traditions have declined, at least a little, as shares of the U.S. adult population since the first RLS was conducted in 2007. The mainline Protestant category has exhibited the sharpest drop, declining from 18% of U.S. adults in 2007 to 11% in 2023-24. Evangelicalism remains the largest tradition within Protestantism, but the evangelical share of the adult population also has ticked down, going from 26% in 2007, to 25% in 2014, to 23% in 2023-24. Respondents in the historically Black Protestant tradition accounted for 7% of respondents in 2007 and 5% in 2023-24 (after rounding to the closest whole number). Because

IBM has announced its intent to acquire DataStax, a leading data platform provider. This strategic acquisition significantly boosts IBM’s AI data platform by integrating advanced vector capabilities critical for powering retrieval-augmented generation (RAG) applications. It positions IBM to help businesses leverage value from vast volumes of unstructured data, an area where IBM lacks a strong foothold. DataStax brings expertise to IBM in distributed databases capable of spanning multiple regions, an essential capability for enabling seamless global AI and data fabric deployments. Also, this acquisition strengthens IBM’s commitment to advancing open-source initiatives with DataStax’s support for the Apache Cassandra database and Langflow, a low-code tool for AI development. What It Means IBM has made numerous acquisitions over the years, but this one stands out as one of the most strategic moves to enhance its data platform, primarily focusing on AI. While IBM has previously acquired database companies, integrating them into its stack has often been slow. The success of this acquisition will hinge on how quickly and seamlessly it integrates with IBM’s watsonx AI platform. This acquisition positions IBM to better compete in the AI space in several key ways by adding: Enhanced support for unstructured data management at scale. While IBM supports unstructured data management with its Db2 offering, it has historically lagged in providing comprehensive and scalable solutions. This acquisition addresses that gap, enabling IBM to offer a more robust suite of AI data capabilities. Apache Cassandra, a schemaless NoSQL database, is designed to handle massive volumes of semistructured data at scale, empowering IBM to deliver a more robust and scalable data platform for AI applications. Strengthened vector capabilities for RAG applications. IBM has lagged in providing the critical vector capabilities that are now essential for powering RAG applications. Built on Apache Cassandra, Astra DB delivers high-performance advanced vector capabilities vital for AI-driven workloads requiring rapid retrieval of high-dimensional data. Recognized as a Leader in The Forrester Wave™: Vector Databases, Q3 2024, DataStax has comprehensive, advanced capabilities. Integrating Astra DB with IBM watsonx.data will significantly enhance its vector capabilities, positioning IBM for greater success in the evolving AI landscape. Enablement for globally distributed data AI environments. DataStax delivers a cloud-native database as a service that simplifies deployment and management and provides a globally distributed data infrastructure ensuring flexibility across multicloud and multiregional environments. As the demand for distributed data continues to rise, this capability significantly enhances IBM’s ability to empower AI-driven solutions on a global scale. Middleware capabilities for IBM watsonx.ai with Langflow. In April 2024, DataStax acquired Logspace, the creator of Langflow — a graphical low-code platform that empowers users to visually design and manage AI workflows. Langflow offers seamless integration with diverse AI models and provides Python-based customization. This acquisition extends the IBM watsonx platform by adding dynamic middleware capabilities, streamlining the creation of advanced generative AI applications more efficiently. Expanded data fabric capabilities with a scalable data platform. IBM has a viable data fabric solution with its IBM Cloud Pak for Data and watsonx.data offerings. With this acquisition, IBM is poised to enhance its data fabric capabilities, supporting both structured and unstructured data at scale while integrating advanced vector capabilities. This expansion is also likely to help IBM deploy AI agents at scale, strengthening its position in the AI-driven data landscape. For more insights, book time with me via an inquiry or guidance session. source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Intuit — the financial software giant behind products like TurboTax and QuickBooks — is making significant strides using generative AI to enhance its offerings for small business customers. In a tech landscape flooded with AI promises, Intuit has built an agent-based AI architecture that’s delivering tangible business outcomes for small businesses. The company has deployed what it calls “done for you” experiences that autonomously handle entire workflows and deliver quantifiable business impact. Intuit has been building out its own AI layer, which it calls a generative AI operating system (GenOS). The company detailed some of the ways it is using gen AI to improve personalization at VB Transform 2024. In Sept. 2024, Intuit added agentic AI workflows, an effort that has improved operations for both the company and its users. According to new Intuit data, QuickBooks Online customers are getting paid an average of five days faster, with overdue invoices 10% more likely to be paid in full. For small businesses where cash flow is king, these aren’t just incremental improvements — they’re potentially business-saving innovations. The technical trinity: How Intuit’s data architecture enables true agentic AI What separates Intuit’s approach from competitors is its sophisticated data architecture designed specifically to enable agent-based AI experiences.  The company has built what CDO Ashok Srivastava calls “a trinity” of data systems: Data lake: The foundational repository for all data. Customer data cloud (CDC): A specialized serving layer for AI experiences. “Event bus“: A streaming data system enabling real-time operations. “CDC provides a serving layer for AI experiences, then the data lake is kind of the repository for all such data,” Srivastava told VentureBeat. “The agent is going to be interacting with data, and it has a set of data that it could look at in order to pull information.” Going beyond vector embeddings to power agentic AI The Intuit architecture diverges from the typical vector database approach many enterprises are hastily implementing. While vector databases and embeddings are important for powering AI models, Intuit recognizes that true semantic understanding requires a more holistic approach.  “Where the key issue continues to be is essentially in ensuring that we have a good, logical and semantic understanding of the data,” said Srivastava.  To achieve this semantic understanding, Intuit is building out a semantic data layer on top of its core data infrastructure. The semantic data layer helps provide context and meaning around the data, beyond just the raw data itself or its vector representations. It allows Intuit’s AI agents to better comprehend the relationships and connections between different data sources and elements. By building this semantic data layer, Intuit is able to augment the capabilities of its vector-based systems with a deeper, more contextual understanding of data. This allows AI agents to make more informed and meaningful decisions for customers. Beyond basic automation: How agentic AI completes entire business processes autonomously Unlike enterprises implementing AI for basic workflow automation or customer service chatbots, Intuit has focused on creating fully agentic “done for you” experiences. These are applications that handle complex, multi-step tasks while requiring only final human approval. For QuickBooks users, the agentic system analyzes client payment history and invoice status to automatically draft personalized reminder messages, allowing business owners to simply review and approve before sending. The system’s ability to personalize based on relationship context and payment patterns has directly contributed to measurably faster payments. Intuit is applying identical agentic principles internally, developing autonomous procurement systems and HR assistants.  “We have the ability to have an internal agentic procurement process that employees can use to purchase supplies and book travel,” Srivastava explained, demonstrating how the company is eating its own AI dog food. Designed for the reasoning model era What potentially gives Intuit a competitive advantage over other enterprise AI implementations is how the system was designed with foresight about the emergence of advanced reasoning models like DeepSeek. “We built gen runtime in anticipation of reasoning models coming up,” Ashok revealed. “We’re not behind the eight ball … we’re ahead of it. We built the capabilities assuming that reasoning would exist.” This forward-thinking design means Intuit can rapidly incorporate new reasoning capabilities into their agentic experiences as they emerge, without requiring architectural overhauls. According to Srivastava, Intuit’s engineering teams are already using these capabilities to enable agents to reason across a large number of tools and data in ways that weren’t previously possible. Shifting from AI hype to business impact Perhaps most significantly, Intuit’s approach shows a clear focus on business outcomes rather than technological showmanship. “There’s a lot of work and a lot of fanfare going on these days on AI itself, that it’s going to revolutionize the world, and all of that, which I think is good,” said Srivastava. “But I think what’s a lot better is to show that it’s actually helping real people do better.” The company believes deeper reasoning capabilities will enable even more comprehensive “done for you” experiences that cover more customer needs with greater depth. Each experience combines multiple atomic experiences or discrete operations that together create a complete workflow solution. What this means for enterprises adopting AI For enterprises looking to implement AI effectively, Intuit’s approach offers several valuable lessons for enterprises: Focus on outcomes over technology: Rather than showcasing AI for its own sake target specific business pain points with measurable improvement goals. Build with future models in mind: Design architecture that can incorporate emerging reasoning capabilities without requiring a complete rebuild. Address data challenges first: Before rushing to implement agents, ensure your data foundation can support semantic understanding and cross-system reasoning. Create complete experiences: Look beyond simple automation to create end-to-end “done for you” workflows that deliver complete solutions. As agentic AI continues to mature, enterprises that follow Intuit’s example by focusing on complete solutions rather than isolated AI features may find themselves achieving similar concrete business results rather than simply generating tech buzz. source

FinovateEurope took place in London again this week, and I was lucky enough to attend. This year marked my 12th Finovate anniversary, making me something of a veteran (or a diehard fan!). Over the years, I’ve witnessed the hype, the growing up, and the reckoning in the sector. While fintech won’t result in full market upheaval, it was exciting to see more energy return to the event this year. Perhaps unsurprisingly, this was mostly thanks to AI. Sure, the event also featured the more usual set of presenters showcasing new digital banking capabilities, personal financial management, or identity authentication (presenter Keyless took home one of the “best of show” awards). But generative AI (genAI) and AI agents stole the show. As my colleague Aurélie L’Hostis (who presented on genAI in financial services) and I compared notes, here’s what stood out: AI promises new breakthroughs in automation. AI is nothing new in financial services and has featured at Finovate before,but this year’s focus on AI agents is new — promising to reshape operating models and value propositions like never before. AI agents can augment humans to support increasing workloads, reduce costs, and improve employee experience. They gather data, initiate inquiries, conduct research, and tackle a range of low- to medium-level cognitive tasks. Despite boasts of agentic AI, most demos focused either on automating specific tasks (e.g., AQ22 with generating an investment or credit memo) or processes but didn’t really show complex multiagent systems capable of adapting to dynamic conditions. Process transformation requires incorporating different AI components — such as chatbots, text analytics for document extraction, and predictive analytics and ML solutions for decision management — and linking them to data and internal apps and systems. For example, Arva AI, Intrepid Fox, and Intuitech speed up new business customer onboarding or loan decisions by using AI to extract and verify information from uploaded documents, validate online presence, search government databases for missing information, and map ownership structures. Many currently augment rather than replace the work of loan or compliance officers by providing reasoning behind alerts or drafting emails for follow-ups. GenAI holds the keys to unlocking legacy system constraints. As we have written previously, TuringBots, AI, and genAI software development assistants are transforming software development by generating code, documentation, and helping with planning, testing, and deployment. Many banking tech leaders are hopeful that TuringBots will help them modernize and migrate legacy applications. However, the most common off-the-shelf TuringBots aren’t well suited to producing new code in very old languages such as Assembler or COBOL or for industry-specific applications such as core banking systems and require additional efforts and skills. For now, Tweezr (another “best of show” winner this year) aims to support developers in navigating legacy code. The company demoed a scenario where a developer tries to create joint account functionality in COBOL. The AI assistant identifies required features, creates technical guidelines, and identifies constraints. Most importantly, the solution guides the developer on what changes to make, where, and how. If successful, this workaround might temporarily lower the pressure that banks face to modernize their legacy. But genAI also drives deepfake fraud. Deepfakes are easier to generate than ever, more convincing than ever, and permeate across all channels (including call center, mobile app, and online web). Protection against deepfakes takes many forms, from protecting the channel to understanding user behavior to looking at artifacts in data that deepfakes present. Lots of vendors are working on developing, testing, and perfecting deepfake defences. At FinovateEurope, Neural Defend demoed one such detection tool for deepfake images, audio, and video. I was excited to see so many great demos and look forward to more! As genAI empowers a new generation of builders with easy software development tools, I expect to see another wave of innovation. Please schedule an inquiry or guidance session with us to discuss trends in this space. source