The next five years will transform communications more dramatically than the previous five decades. Here are 5X: five seismic shifts that are reshaping the future of our profession. The Attention Economy: Earned renewal. The strategy: Companies can’t buy attention the way they used to — they must earn it by creating ideas that move through culture, not just media. The impact: Winning ideas spread because they let people express their identity and values. Breakthrough concepts don’t just reach communities — they form them. The Creator Economy: Influence redefined: The new reality: Brands must co-create with those who shape culture, measuring actual influence over vanity metrics. Why it’s important: Creators increasingly drive earned strategies, capturing attention that attracts traditional media coverage and fuels broader cultural conversation. The Stakeholder Economy: Business meets culture. The Experience Economy: Digital, integrated: What this means: Audiences, who increasingly live their waking hours connected, expect personalized, participatory experiences across physical and digital touchpoints. Moments must be felt, not just seen. The breakdown: The companies that succeed in this AI generation will look nothing like those that succeeded in the last one. If you haven’t changed your playbook, you’re already behind.
AI is setting the idea of four-day work into action by allowing firms to share the gains of improved technology and giving workers some of their time back with no change in pay
The idea of four-day work week is gaining traction among proponents of the four-day work week, and at least one software startup CEO has moved his company to a 32-hour week — with no change in pay — because of AI. Sen. Bernie Sanders (I-Vt.) is a four-day work week booster, having introduced a 32-hour workweek bill last year, though such a proposal is unlikely to get far in Congress. Instead of firing people, proponents argue that firms share the gains of improved technology by giving workers some of their time back. Instead of fearing AI will replace them, workers welcome its advancements and figure out creative ways to leverage the tech. Economist Juliet Schor, lead researcher for 4DWG, a global nonprofit that’s piloted shorter work weeks with 245 organizations in the U.S., U.K. and elsewhere says “The ability of large language models like ChatGPT to wipe out millions of good-paying positions means we need to be intentional about how we adjust to that technology. Reducing hours per job is a powerful way to keep more people employed.” Smaller firms can more easily implement a big change like a four-day week — larger companies are likely to have a harder time making it happen, experts say. But reducing work hours to make sure a lot of people don’t lose their jobs when technology advances isn’t a new idea. Shortening work hours as a way to reduce unemployment was one of the arguments wielded by advocates for five-day work weeks back in the early 20th century. (That used to be a wild idea, too.) Roger Kirkness, the CEO of a small software startup called Convictional moved the company to a four-day workweek — without reducing anyone’s pay. Kirkness tells that using AI accelerates writing code but it doesn’t speed up everything — teams still need to be able to think creatively to solve problems and get real work done. The four-day work week is meant to keep everyone fresh, with enough time to recharge so they can do deep-thinking.
Report reveals new gen AI models typically spend three weeks at the top of the usage charts and then drop off as new open-source rivals emerge with frontier models depreciating on a 6–12 month timescale
Generative AI has entered the mainstream faster than any previous new technology. But the tech industry hasn’t yet figured out the best ways to build AI products — and fierce competition, along with rapid advances, means nobody stays at the top of the heap for long. Those are some of the top-line findings of a new report on the state of AI foundation models from Innovation Endeavors, the venture capital firm co-founded in 2010 by former Google CEO and chairman Eric Schmidt. The report says that 1 in 8 workers globally now uses AI on a monthly basis. 90% of that growth took place in the last six months. New models regularly topple technical benchmarks, but the cost of training them is also ballooning. “The average duration of human task a model can reliably do is doubling every seven months,” per the report. New models typically spend three weeks at the top of the usage charts and then drop off as newcomers emerge and open-source rivals absorb and commoditize their advances. Frontier models “depreciate on a 6–12 month timescale,” the report says. AI is “fundamentally disrupting” software development and collapsing the distinctions between programming, product management and design, the report also finds. Therapy, life organization and learning” lead the list of general-interest AI use cases.
New campaign spotlights neurodivergent talent as a token effort, but to reposition it as essential to the future of the creative industry
New global campaign by Havas, Beyond the Brief, launched live at the 2025 Cannes Lions International Festival of Creativity, was designed not to spotlight neurodivergent talent as a token effort, but to reposition it as essential to the future of the creative industry. Helmed by Donna Murphy, Global CEO of Havas Creative and Health Networks, the campaign builds on the foundation of Neuroverse: Powered by Havas, aiming to shift how the industry identifies and cultivates creative potential radically. The campaign’s anchor panel was named “Neurodivergent Minds: They Don’t Need Advertising. Advertising Needs Them.” Days before the launch, unbranded digital teaser displays appeared along the Croisette, posing provocative questions like, ‘What if the future of creativity doesn’t look like the past, and never did?’ Each display featured a QR code that led to a dedicated microsite with a full agenda of neurodiversity-focused programming, including featured panels, downloadable insights, and events hosted beyond Havas. The campaign also highlighted that neurodivergent people are more than just creative contributors; they’re also a critical consumer demographic. A session at the Havas Café titled “The New Creative Alchemy: Neurodivergent Minds & AI as Industry Catalysts” offered a roadmap for how brands and agencies can better support neurodivergent talent and create products and campaigns that resonate with their experiences. “With Beyond the Brief, we’re looking to amplify these voices and challenge the industry to rethink the systems in place,” Murphy emphasized. By debuting the initiative at the largest creative festival in the world, she made it clear that this wasn’t about corporate social responsibility; it was about redesigning the very ecosystem of creativity. Too often, neurodivergent candidates are excluded not because they lack.
Embedded Finance 2.0: SaaS platforms are chasing banking charters, adopting multi-tenant model for splitting deposits and baking compliance features such as automated KYC and ledger-level reporting into the API call
Embedded Finance 2.0 is where the “Pay” button graduates into a full on-platform treasury desk and the question morphs from Can we process a payment? to Should we hold your cash? First, the deep-pocketed few will likely chase full-fat charters. Intuit already controls an OCC-granted industrial loan company, and rumor has it Shopify is exploring a Canadian Schedule I license so it can plug directly into FedNow and CAD settlement rails. Owning the license erases sponsor fees, provides direct central-bank access and turns Fed holidays into just another dashboard metric. It also drags CEOs into capital-ratio land, where quarterly stress tests replace flashy conference-stage keynotes. Second, mid-tier platforms are furiously diversifying sponsors. Stripe quietly maintains half a dozen partner banks across continents; Adyen splits deposits between its European and U.S. charters so funds never cross jurisdictions. A multi-tenant model may mollify supervisors who now demand credible “if-this-bank-fails” exit plans. It also means engineering teams must reconcile half a dozen core-banking APIs before morning coffee—a non-trivial tax on velocity. Third, a new generation of BaaS providers such as Unit, Treasury Prime, and Griffin, is selling compliance as the actual product: automated KYC, ledger-level reporting, FDIC-ready dashboards baked right into the API call. The value prop is clear—“Let us worry about Section 314(b) so you can focus on restaurant software”—but only holds if the RegTechs stay ahead of evolving rules. If they lag, their SaaS clients inherit the audit headache anyway. If Embedded Finance 1.0 merely added a Pay button, 2.0 aims to become the balance sheet. The platforms that survive will treat compliance as a feature, not a cost center. That means real-time ledgers auditors can query in a single GET request, FedNow and SEPA Instant wired in at the kernel, and credit models transparent enough that supervisors nod before shareholders cheer. SaaS founders used to brag about daily active users; tomorrow they might brag about their Liquidity Coverage Ratio. The irony would be delicious if it weren’t so expensive. Once embedded finance volumes crest half-a-trillion dollars, systemic stability demands oversight inside the platforms where money truly lives. The badge on your business debit card might one day read Shopify, Toast or Xero—but the compliance brain under the hood will need to think, grizzled and cautious, like JPMorgan.
OpenAI’s API platform allows developers to express intent, not just configure model flows through built-in capabilities for knowledge retrieval, web search, and function calling for supporting real-world agent workflows
Olivier Godement, Head of Product for OpenAI’s API platform, provided a behind-the-scenes look at how enterprise teams are adopting and deploying AI agents at scale. According to Godement, 2025 marks a real shift in how AI is being deployed at scale. With over a million monthly active developers now using OpenAI’s API platform globally, and token usage up 700% year over year, AI is moving beyond experimentation. Godement emphasized that current demand isn’t just about chatbots anymore. “AI use cases are moving from simple Q&A to actually use cases where the application, the agent, can do stuff for you.” This shift prompted OpenAI to launch two major developer-facing tools in March: the Responses API and the Agents SDK. Some enterprise use cases are already delivering measurable gains. Godement positioned the Responses API as a foundational evolution in developer tooling. Previously, developers manually orchestrated sequences of model calls. Now, that orchestration is handled internally. “The Responses API is probably the biggest new layer of abstraction we introduced since pretty much GPT-3.” It allows developers to express intent, not just configure model flows. “You care about returning a really good response to the customer… the Response API essentially handles that loop.” It also includes built-in capabilities for knowledge retrieval, web search, and function calling—tools that enterprises need for real-world agent workflows. Some enterprise use cases are already delivering measurable gains: Stripe, which uses agents to accelerate invoice handling, reporting “35% faster invoice resolution; ” Box, which launched knowledge assistants that enable “zero-touch ticket triage.” Other high-value use cases include customer support (including voice), internal governance, and knowledge assistants for navigating dense documentation. Godement offered a glimpse into the roadmap. OpenAI is actively working on: Multimodal agents that can interact via text, voice, images, and structured data; Long-term memory for retaining knowledge across sessions; Cross-cloud orchestration to support complex, distributed IT environments. What matters now is building a focused use case, empowering cross-functional teams, and being ready to iterate. The next phase of value creation lies not in novel demos—but in durable systems, shaped by real-world needs and the operational discipline to make them reliable.
Study finds running gen AI models on the phones instead of in the cloud consumed anywhere from 75% to 95% less power, with associated sharp decreases in water consumption and overall carbon footprint
One of the easiest ways to minimize AI’s environmental impact may be to move where the processing is done, per new academic research conducted in partnership with Qualcomm. Running AI on devices instead of in the cloud slashes power consumption of queries by about 90%, the study finds. The industry has long touted the benefits of running models locally on devices instead of in the cloud — not just in energy terms, but also potentially making them cheaper and more private. Researchers at the University of California, Riverside ran a series of experiments comparing the performance of various generative AI models, both in the cloud and on phones powered with Qualcomm chips. Running any of six different models on the phones consumed anywhere from 75% to 95% less power, with associated sharp decreases in water consumption and overall carbon footprint. Qualcomm is also developing an AI simulator and calculator that illustrates, for any given query and user location, what the responses would look like on-device versus the cloud, and how much less power and water they would use. One example — running a coding skills question on the Llama-2-7B model in California — was 94% more power efficient and 96% more water efficient on-device. For all six models in the study, the inference time on the phones, measured in seconds, was higher than in the cloud. Narrowing or eliminating that gap, particularly on the most powerful and popular models, will be crucial to accelerating on-device adoption. For many AI users, the data center in your pocket might be all you need.
Volcano Exchange’s financial RWA digital asset leverages blockchain tech to transform high-threshold private banking services into divisible and tradable digital assets lowering the entry barrier for retail investors
Volcano Exchange (VEX), a global digital trading platform for Real World Assets (RWA), today announced the official launch of its first financial RWA digital asset–HL (Morgan Stanley Private Wealth RWA Token). Backed by the future returns of Morgan Stanley Private Bank’s premium wealth management products, HL has a total issuance of $20 million, corresponding to 200 million HL tokens, with an initial subscription price of $0.1 per token. This issuance marks a deep integration of traditional finance and blockchain technology, offering global investors more transparent, efficient, and flexible digital asset trading and staking services. HL is VEX’s first RWA digital asset underpinned by the revenue rights of a traditional financial institution, with its value directly pegged to the future earnings of Morgan Stanley Private Bank products. Leveraging blockchain technology, VEX transforms high-threshold private banking services into divisible and tradable digital assets, lowering the entry barrier for retail investors while maintaining the stability and compliance of traditional finance. With a total supply of 200 million tokens, HL is available for subscription on the VEX platform at an initial price of $0.1 per token. After the subscription period concludes, HL will be officially listed for trading, becoming VEX’s first RWA digital financial trading pair. Holders can freely trade on secondary markets or participate in value-added services such as staking and lending through VEX’s digital finance sector, maximizing asset liquidity. The launch of HL represents a major milestone in the RWA space. By digitizing traditional financial assets through blockchain technology, we enhance their liquidity and composability. Moving forward, VEX will continue to onboard premium assets from top-tier institutions, building a global RWA financial infrastructure.
VanguardX Finance Institute’s platform uses logic, adaptability, and scenario planning to highlight structured market entries and exits through contextual logic analysis and simulates execution strategies across shifting economic conditions
VanguardX Finance Institute announces the launch of VanguardX Mind, a structured decision-making platform developed under the leadership of Charles Laurence. The system integrates strategic modeling, simulation, and scenario-based learning to enhance investment reasoning across market conditions. VanguardX Finance Institute has officially launched VanguardX Mind, a comprehensive trading and strategy development system designed to strengthen the connection between investment education and real-world decision-making. Developed under the direction of Professor Charles Laurence, the platform introduces a new paradigm for structured financial training built on logic, adaptability, and scenario planning. VanguardX Mind is comprised of four core modules engineered to foster strategic clarity and cross-cycle awareness:
- Trading Signal Decision System – Highlights structured market entries and exits through contextual logic analysis.
- Programmatic Execution Module – Simulates execution strategies across shifting economic conditions.
- Investment Strategy Decision Engine – Supports multi-variable evaluation of sectoral and thematic opportunities.
- Expert and Advisory System – Delivers high-level insights to support advanced learners and institutional participants.
Unlike traditional passive instruction models, VanguardX Mind has been fully embedded into the instructional design of VanguardX Finance Institute, encouraging students to build, test, and refine personalized investment strategies. Emphasis is placed on real-time feedback, post-trade review, and modular decision architecture. The platform is targeted toward emerging strategists, institutional analysts, and mid-career professionals seeking practical command over capital deployment and market interpretation. VanguardX Mind supports users in navigating volatility, identifying regime shifts, and maintaining strategic discipline under pressure.
Robinhood launches micro crypto futures for Bitcoin, Solana and XRP to enable retail investors and casual traders to speculate on price movements or hedge positions with reduced risk exposure and significantly less capital
Robinhood (NASDAQ: HOOD) has launched micro crypto futures for Bitcoin (BTC), Solana (SOL), and XRP in the U.S., expanding its futures trading suite for over 26 million funded users. This move adds to its January rollout of full-sized BTC and ETH futures, providing retail investors with lower-barrier access to crypto derivatives. Micro futures contracts require significantly less capital than traditional futures, allowing traders to speculate on price movements or hedge positions with reduced risk exposure. These smaller contracts offer greater flexibility and are aimed at making futures trading more accessible to a broader user base. Robinhood’s internal data highlights growing crypto activity on the platform, with notional trading volumes reaching $11.7 billion in May 2025. That figure represents a 36% increase from April and a 65% year-over-year surge, indicating strong retail interest in cryptocurrency markets. As crypto adoption continues to grow, Robinhood’s introduction of micro futures positions the firm to better serve both casual traders and more experienced investors seeking diversified trading tools. By lowering the entry threshold, Robinhood aims to capture more trading activity while promoting responsible participation in the volatile digital asset market. With these micro futures, Robinhood is solidifying its role as a major player in crypto derivatives trading, enhancing its competitive edge and expanding access to key digital assets like Bitcoin, Solana, and XRP.
