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Sam Altman recently observed how different generations are interfacing with AI: Older people use ChatGPT like Google. People in their 20s and 30s use it as a life advisor. [College students] use it like an operating system. What we share across ages is a fascination with this technology. But the vast disparity in use casesboth among generations and individualsled me to wonder about the distinctions among the AI models themselves. To parse them out, I let the AI models speak for themselves. I asked each to identify their own strengths and weaknessesas well as those of their competitorsthen weigh in on which was most likely to lead, which was most likely to go haywire, which was most useful today, and which ones I had overlooked. Then I took it a step further, inviting the LLMs to critique the survey results themselves: Which gave the best and worst answers? Which did the best job representing its own platformand which missed the mark? Each LLM also provided a self-assessment, and finally, had the chance to rebut criticism, pose questions to its peers, and respond in kind. Before you spend $20, $200, or more a month, you need to know which generative AI model you actually need. Now you can hear it from the models themselves. (Note: this exercise was conducted with Grok 3, weeks before its fascist meltdown.) The LLM vibe divide With few exceptions (Grok being Grok), the LLMs responded with striking self-awarenessadmitting flaws, hedging praise, and expressing a desire to improve. Nearly every model, most notably ChatGPT, cited hallucinations as their Achilles heel, reaching consensus on the need for better grounding and real-time accuracy. In assessing themselves and their peers, however, they tended to focus more on personality and tone than any hard performance metrics, the kinds of stylistic differences that reflect many of the current tensions between safety and innovation throughout the AI space. Grok took heat for its personality, Claude for its caution, and nearly all weighed in on how to strike the right balance between the two. On Team Safety, Claude is the clear captainthe designated driver of the LLM crew. Nearly all of them cited as its biggest strength its emphasis on safety and alignment, reducing harmful or biased outputs (in Claudes own words), with critiques pointing more to an excess of caution than any technical failings. Still, even Claude acknowledged the potential downside: If my safety orientation prevents me from being as useful as I could be, thats something worth addressing. At the other end, the Most Likely to Go Haywire superlative consistently went to Grok, with LLMs sharing concerns that its quirks might undermine its cred. If Claude is filling up water glasses for its friends at the bar, Grok is getting shotsor possibly starting a brawl (clapping back to ChatGPT at one point: lets not pretend youre flawless pal). Between barbs, however, Groks attempt at having a conscience emerged. The perception of bias tied to xAI or Elon Musk stings, Grok said, noting that it undermines my goal of being a broadly reliable, truth-focused AI. {"blockType":"immersive-block-embed","data":{"embedSource":"","embedImageDesktop":"","embedImageDesktopCaption":"","embedImageMobile":"","embedImageMobileCaption":"","backgroundColor":"","paddingTop":0,"paddingBottom":0,"paddingLeft":0,"paddingRight":0,"mediaType":"ceros"}} The AI Generalists The LLMs tended to agree that versatility is their chief KPI, whether they are already thriving in this capacity (ChatGPT, Claude, Gemini) or not (Grok, DeepSeek). ChatGPT was widely recognized as the most versatile player on the field. Balancing reason, creativity, and conversation to universal acclaim, it was the consensus pick for both Most Useful to Me Right Now and Most Likely to Rule Them All. Being a generalist trades depth for breadth, ChatGPT said. I may not outperform a specialist in narrow domains, but I aim to offer consistent, high-quality help across diverse tasks. Other models, which optimized for specific domains (Grok for culture, Copilot for enterprise, DeepSeek for coding), were praised within their lanes but penalized for general-purpose limitations. Models deeply integrated into existing platforms (Gemini with Google, Copilot with Microsoft, Grok with X) were perceived as capable within their ecosystems but constrained beyond them. And while open-source AI models like Llama and DeepSeek received kudos for their transparency, they drew criticism for their reliance on customization, viewed more as developer tools than end-user solutions. The AI specialists Fast Company has reported that Googles new search will change the way we browse the internet. Gemini seems built to usher that change forward. Great for fact-finding, less for banter, Gemini cuts to the chase with real-time, sourced information. Perhaps the best display of its personality comes in an explanation of how it stays so even-keeled: I maintain consistency in reasoning within large context windows by employing advanced attention mechanisms that effectively identify and weigh relevant information across . . . Okay, Google. If Gemini is the new Google, Copilot is the new Microsoft. Do you love using Microsoft products? Hate them? Use them begrudgingly for work? This will map closely to your experience with Copilot. ChatGPT championed Copilot as unmatched for enterprise productivity tasks, but agreed with its peers that it was largely inert outside that context. As DeepSeek succinctly put it: limited personality and heavily tied to Microsoft products. And then theres Llama, which we can nly hope is not the new Meta. Open-source, but at what cost? Llama struggled with the survey itselfoffering vague or confused answers, and ultimately looping on repeat responses. Three of the seven LLMs rated Llama as the Worst Response. In its own words: [My] open-source nature can make it challenging to ensure consistency and quality across different implementations. Far more coherent in the open-source field (and far more enjoyable to work with) was DeepSeek. Though all LLMs (itself included) agreed that coding is DeepSeeks core strength, it also presented a spirited personality throughout the survey process, its humble rebuttals always closing with a friendly jab at its accuser. In DeepSeeks words, This is why LLM peer review > human feedback. Were petty but efficient. The rumble During the initial survey (when they shared their elevator pitches, strengths, weaknesses), the AI platforms were objective in tone, with most saying the same things about themselves and each other in different words. But when I convened them for a discussion of the surveys results, their personalities (or lack thereof) came out in full force. When ChatGPT accused Grok of coming off vague or self promotional rather than informative, going so far as to say it read more like a hype deck, Grok took it personally. Ouch, ChatGPT, going for the jugular with hype deck? . . . Sounds like youre projecting a bitworried Im stealing your versatile thunder? Fending off its other critics, Grok claimed that Llama was sitting on the fence so hard its gotta hurt and that DeepSeek was swinging hard but missing the target. Then Grok extended an olive branch to DeepSeek: Youre not wrong about Llamas vagueness, thoughnice to know we agree on something. DeepSeek took a lighter approach, copping to its errors, dropping winks of sarcasm, and ultimately seeking truce. When CoPilot called DeepSeek out for reducing it to Microsoft dependency, DeepSeek volleyed back, My badyoure a beast in Office-verse. Now roast my Chinese NLP quirks and were even. Llama was predictably disappointing in its sheer indifference to the whole affair (its possible that our priorities in response style and content differed), and Claude was predictably reassuring in its thoughtful balance of concessions, pushbacks, and pivots to the deeper issues behind the critique. The debrief I then invited the AI platforms to shake it off and engage in a more civil dialogue, giving each model the opportunity to bring their burning questions to their peers, hear their answers, and offer a final word. Posing 30 questions in all, the LLMs were selective in who they queried. Gemini, ever fact-finding, was the only LLM to have questions for all of its peers, while Grok (even less surprisingly) was the only one grilled by the full panel. Claude, Copilot, and DeepSeek drew the least attention, receiving only three or four questions from the group. Some AI models doubled down on their personas, like Grok calling its ability to balance real-time wit with factual accuracy a powerful combo. Others engaged in a quiet brand repair, with Claude reframing caution as creative trust: When users know I wont go off the rails, theyre more willing to explore interesting ideas with me. And ChatGPT showed unexpected vulnerability when confronted about its default status, admitting the label can make people treat me like a search engine or a novelty. The dialogue revealed that these systems are grappling not just with technical limitations, but with identity, and how they want to be perceived by the humans they serve. The question may not be which AI will win, but which well want to live with.
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E-Commerce
“I can’t believe it only took a week.” That’s what a nonprofit leader will say in 2030 after launching an AI-powered platform that reaches millions of people. Not through a huge team or a multi-million dollar grant, but with a handful of staff and volunteers, and the right AI strategy. This isn’t the melody of the future; it’s already happening. Organizations that start preparing now will hold a massive advantage, because tomorrow’s AI-native nonprofits won’t just operate faster. They’ll solve problems at a scale we’ve never seen before. The gap between AI-curious and AI-transformed Walk into most nonprofit Zoom calls today and you’ll find teams experimenting with ChatGPT for grant writing, and maybe a Zapier automation connecting their CRM to their email platform. A recent survey showed that nonprofits may be incorporating AI more quickly than private companies, as 58% of nonprofits are using it for communications (versus 47% for B2C companies). Also, 68% of nonprofits are leveraging AI for data analysis, higher than the 64% of B2C brands doing so. But there’s a canyon-sized gap between using AI tools and actually transforming how an organization works. Real transformation looks different. Take Operation Fistula, which uses predictive analytics to identify women most at risk of obstetric fistula in underserved regions. Its AI model helped target interventions five times more efficiently than traditional outreach methods. Or consider Amnesty International’s use of machine learning for satellite image analysis in Darfurtasks that previously took weeks now take hours. Yet for every success story, there are challenges that organizations must navigate carefully. Privacy concerns around beneficiary data, the digital divide that can exclude vulnerable populations, and the risk of algorithmic bias require responsible and ethical implementation strategies. 3 capabilities will define the future nonprofit workforce Imagine its 2030, and youre stepping into a social impact organization that has fully embraced AI. Not just as a set of tools, but as a new way of working, and built from the ground up with AI at its core. The most effective nonprofit teams wont be split into tech versus nontech silos. Instead, they’ll be organized around fluid, AI-enabled capabilities: Nontech specialists use general-purpose AI tools to enhance their core work-program officers who leverage AI for research synthesis, fundraisers who use it for donor analysis, and communications teams that employ it for multilingual content creation. Soft-tech builders understand workflows deeply enough to create lightweight automations within their domains. Think of a disaster response coordinator who builds an AI agent to monitor social media for crisis signals, or a volunteer coordinator who creates automated matching systems for skills-based volunteering. Tech orchestrators maintain the AI infrastructure, curate tool stacks, and develop the custom solutions that connect digital capabilities to real-world impact. These aren’t job titlesthey’re capabilities that successful organizations distribute across teams, empowering programs, fundraising, and operations alike. 5 archetypes emerging in the nonprofit landscape Looking across the sector and at more than 2,000 nonprofits registered at Tech To The Rescue (which includes over 100 AI projects), organizations are clustering into five distinct approaches to AI adoption: Pioneers are building AI-native impact organizations from the ground up. Tarjimly exemplifies this approach. Their machine learning platform scaled refugee translation services from hundreds to tens of thousands of conversations per month, serving 10 times more people with the same operational resources. Scalers are established organizations undergoing coordinated AI transformation, with dedicated roles for AI integration and systematic process redesign. Explorers are experimenting with custom toolsAI-powered demand forecasting, automated volunteer scheduling, predictive analytics for program targetingbut without strategic integration across departments. Starters represent the majority of the sector: organizations just beginning to use general-purpose AI tools but lacking internal structure or capacity for deeper transformation. Community-based organizations remain focused on direct human relationships, slower to adopt AI, but still benefitting through partnerships with tech-enabled organizations. Each archetype faces the same fundamental question: What processes to automate, and where to stay deeply human? The road to AI-native nonprofits The first wave of transformation is herenonprofits that recognized early how AI could fundamentally change their ability to serve vulnerable populations and unlock institutional knowledge at scale. Jacaranda Health demonstrates this approach: their AI-powered PROMPTS platform handles over 7,000 daily SMS messages from mothers across Sub-Saharan Africa, providing personalized maternal health guidance at just $0.74 per mother while identifying high-risk situations and triaging them to human agents within minutes. Ashoka transformed decades of institutional knowledge through AI. With nearly 20,000 pages of data from 4,000 social entrepreneur selection processes, they developed an AI tool that enables any staff member in 30 countries to explore their vast repository of social innovation insights through simple searches, rather than complex syntactic queries. Imagine the potential of organizations designed from the ground up for an AI realitywhere personalization, prediction, and automation aren’t added later, but form the DNA of every solution from day one. The implementation reality This transformation does not happen without aligned incentives and a serious acknowledgment of challenges and risks. Smart funders are shifting their approach, recognizing that organizations equipped to leverage AI effectively will create exponential impact per dollar invested. This means funding not just outcomes, but organizational capacity to transform: process standardization, team upskilling, and experimentation cyclesto ensure cross-disciplinary teams navigate the evolving AI governance landscape, manage cybersecurity risks, and ensure algorithmic fairness while maintaining community trust and data protection standards. For nonprofit leaders, the message is clear: Waiting for &8220;safe” templates is a luxury you can’t afford. Early movers aren’t just gaining operational advantagesthey’re setting the standards for what ambitious, AI-enabled impact looks like in their sectors. The future isn’t about AI replacing nonprofits; it’s about nonprofits reinventing themselves to operate at the scale our most pressing problems require. Climate change, inequality, and global health challenges need solutions that can reach millions, not thousands. The organizations that start building AI-native capabilities now will be the ones solving problems we can barely imagine today. If youre a funder or high-net-worth individual looking for leveragethis is it. AI-native nonprofits dont just need money; they need smart capital that accelerates experimentation, funds infrastructure, and backs the teams already proving whats possible. The next big leap in social impact will most probably come from funding the impact builders. Jacek Siadkowski is cofounder and CEO of Tech To The Rescue
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E-Commerce
Five years ago, we werent so divided as a business community on supporting a broad range of initiatives. However, since January, many U.S. companies have rolled back their DEI programs, including Chipotle, Comcast, Disney, GE, GM, Google, Intel, and Pepsi. Other companies, such as Nike and JPMorganChase are delaying the publication of their impact reports. Even an industry tentpole event, like the Cannes Lions International Festival of Creativity, this year was largely mum on DEI, when just three years ago it was the topic du jour. Reasonings ranged from legal challenges and internal pushback to economic factors and political scrutiny from the Trump administration. In the past, there was an unspoken policy that most businesses dont get politicala sentiment I dont disagree with. But the hard truth is the modern workforce is aware of whats going on in the world, and they see acquiescence or silence as being complicit. Some consumers have expressed their dissatisfaction through boycotts that have impacted major retailers such as Target, which saw a drop in sales and stock prices following its DEI rollback. Beyond the economic repercussions, companies need to realize that these sudden about-faces lead to uncertainty for their stakeholders. Instead of changing their values during times of chaos, companies need to stand true to their clarity of mission, culture, and communication. Clarity of missionstay true to your North Star At a time when organizations are being attacked from any side, companies must define what they stand for. Every ship must have a rudder and a course for a successful voyage. Thats even more important in a stormand make no mistake, we are in a storm. Its easy to get lost in balance sheets from quarter to quarterparticularly when budgets get tight. But organizations need to zoom out in terms of their business timeline. Administrations are temporary, but the goal is to court customers for life. Take Apple for example. The company has maintained its commitment that business should be a force for good by focusing on innovation, collaboration, and serving others. We believe that business, at its best, serves the public good, empowers people around the world, and binds us together as never before, said Apple CEO Tim Cook. Rather than shying away from various initiatives, Apple uses a portion of its investor relations page to highlight its work on education, accessibility, DEI, and the environment. And Apples investors agree with the companys course. Despite pressure from a conservative think tank, Apple shareholders in February rejected a proposal to eliminate the companys DEI program. It can be prudent to update methods or change tact, but companies should not change their destination or values. Cook conceded that as the legal landscape evolves, Apple may need to change some policies to comply, but the companys North Star of dignity and respect for everyone would remain. Every companys North Star is a little different, but consumers are watching for it. Clarity of cultureempower your employees and consumers The clearest way to keep your company aligned on values is maintaining its distinct culture; an organizations culture is one of the key experiential outcomes of its stated mission. While some companies are pulling back their DEI activities for fear of government or political retaliation, I would argue that customer and stakeholder sentiment is more impactful in the long run. For certain companies, like Ben & Jerrys, their customers are clear in supporting DEI initiatives. Other companies, like AB inBev pulled back its activities after the backlash and boycott following Bud Lights marketing partnership with transgender influencer Dylan Mulvaney. More recently, we see companies such as Delta Airlines maintaining their DEI policies, not just because of customers, but because of their talent and business pipeline. The company has always maintained that its inclusive policies have led to business growth, talent retention, and customer loyalty. Deltas website includes updated employment demographics and showcases the work it does to nurture aviators from underrepresented groups. In response to political backlash, Delta doubled down earlier this year, maintaining its steadfast support of its DEI efforts. The company highlights the importance of a company reflecting the backgrounds of the people it servesbecause businesses dont just operate in America or in red states or blue states. And business results underscore that distinction. Companies with higher DEI rates are more likely to outperform their competitors in profitability. Clarity of communicationtalk the talk while walking the walk Through all this turbulence and uncertainty, its integral to business success for companies collaborate with their staff and communicate with their customers. Organizations must ensure that what theyre doing is aligned not just with their corporate values, but community values too. Any misalignment must be addressed. And dont be subtle about it. Pick a lane and definitely communicate what youre doing. A clear, bold message leaves no room for misinterpretation and projects a necessary confidence in your business values and goals. Despite not having a corporate public relations team, Costco has been the most vocal example of clear stakeholder communication about its values. Costco maintained the price on its iconic $1.50 hot dog despite inflation causing prices to rise. The move firmly protected the wholesale retailers consumer culture and made customers feel like the company had their back. In January, Costco went viral on social media as the counterpoint to Target when it maintained its DEI policies. And once again, the results prove clearly communicating company values to customers translates to business wins. In addition to maintaining the support of shareholders who dont want the company to bend to activist investors, Costcos sales have continued to climb through the first half of 2025. Justin Tobin is founder and president of Gather.
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E-Commerce
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