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In the next 24 months, your most valuable customer may never visit your site, click your ad, or read your email. Imagine this scenario: You have a lake holiday coming up in two weeks. Instead of manually researching a new set of water skis, scrolling through reviews, and comparing prices, your AI agent handles this task. It scans your calendar to confirm the trip dates, checks the destination and expected conditions, then pulls data from your smartwatch to understand your height, weight, and skill level. It knows your brand affinities, your budget, your shipping constraints, and your preferred colors. Within seconds, it selects the perfect skis, ensures theyll arrive in time, and purchases themno endless open tabs, no second-guessing, no friction. This isnt sci-fi. Its the next wave in digital commerce, and brands that dont adopt now will fall off the digital shelf. If your brand isnt optimized for AI agents, its already losing. Think of AI agents as hyper-loyal personal shoppers but with perfect recall and zero patience for friction. Agents dont care how beloved a brand is. They just care about the data. The primary shopper your brand must persuade into purchasing will no longer be a person, but an AI agent acting on that persons behalf. The traditional marketing funnel is irrelevant in a world where agents compress it into a single millisecond. These autonomous agentic AI systems ingest a customers preferences, constraints, and history, then compress the entire marketing funnel, from awareness to consideration to checkout, into a single, split-second decision. If AI agents are the future of digital commerce, then the checkout process becomes even more critical. Its one of the last, and sometimes only, moments where brands have permission to show up. That means relevance is what keeps you in the consideration set. Most brands market to people. Those days will soon be gone as reasoning-capable agents are beginning to transact, not just inform. A vacation that once required hours of research can now be booked end-to-end in moments, with flights, hotels, and dinner reservations stitched together by code, not clicks. To thrive in this agent-first landscape, brands must reengineer how they surface, price, and prove value, because the algorithms will do the selecting long before a human ever sees the options. AI agents are a new distribution channel SEO alone wont cut it in the agentic world. AI agents arent browsing like humans; theyre retrieving, evaluating, and transacting based on clean, structured data. With 42% of U.S. businesses already paying for AI tools, the infrastructure to support agentic interaction is rapidly being normalized across enterprise stacks. On top of that, the consumer mindset is catching up with the infrastructure as ChatGPT is one of the fastest growing platforms of all time, reaching 100 million users in just two months. To remain in the consideration set, brands must optimize not just for discoverability but for the entire purchasing journey. That means building for machine experience the same way brands once built for user experience. Agents will become distribution endpoints, not unlike marketplaces or search engines, except theyll be personalized and always-on. Product information, pricing, and availability must be structured and accessible via APIs or structured feeds, not buried in formats or siloed systems that cant be read by AI. Brands that view agent-friendly infrastructure as a key growth lever are poised to grab an outsize share of voice and revenue on whats quickly becoming the new algorithmic shelf. Loyalty from both humans and agents Loyalty must be earned on two fronts: emotional and algorithmic. In a world where AI agents can ruthlessly parse thousands of SKUs in mere milliseconds, emotional storytelling may no longer get the job done. Agents will weigh product attributes against shipping timelines, historical pricing data, and ratings volatility with surgical precision. Subpar signals can cause a product option to be filtered out, no questions asked. What does this mean for brands? More than anything, they must operationalize loyalty across two separate but equal fronts: one emotional, and one algorithmic. For human shoppers, loyalty is still earned through rich brand experiences and tailored-to-you storytelling. Agents, on the other hand, demand a very different kind of digital courtship: high-quality, structured data, consistently reliable fulfillment, competitive pricing, seamless checkout with relevant upsells, and gold-star customer satisfaction signals. Brands that win both the hearts and algorithms wont just lead; theyll lock out the competition. For shoppers with only a tenuous connection to your brand, AI agents are your best shot at winning them over, if your data can back it up. Advertising to agents Marketing to machines doesnt require charm, it demands cold structured truth. Unlike people, agents cant be charmed or cajoled by creativity, only swayed by real-time relevance and quantifiable value. That forces a rethink of how brands allocate their media dollars. Traditional ad strategies that have been optimized for human psychology will need a parallel track for performance-driven, machine-readable messaging. In this new paradigm, advertising becomes less about storytelling and more about signaling. These agents wont merely browse, theyll retrieve, rank, and decide. Thats why advertising must evolve to speak their language: real-time product availability, structured metadata, and machine-readable signals. The agent economy is no longer speculative, its investable. To stay in the consideration set, brands must act now to build a data-first infrastructure, prove performance integrity, and become fluent in the language of machines. Agent-based advertising isnt a futuristic niche; its the next frontier of performance marketing. It demands precision, agility, and real-time truth. Because in an agentic world, every brand is constantly reevaluated. Relevance isnt a campaign. Its a living negotiation with algorithms in the drivers seat. Elizabeth Buchanan is chief commercial officer of Rokt.
Category:
E-Commerce
We are in a once-in-a-generation moment. AI isnt just changing how people workits pushing companies to rethink how theyre structured, how decisions get made, and who gets to lead. Our annual Work Trend Index report reveals the stakes: While 81% of women leaders say their company must adopt AI to stay competitive, fewer than half feel they have the resources to drive real impact. Additionally, our research found that men are more likely to use AI at work, trust it with high-stakes tasks, and worry less about being replaced by it. Knowing this matters, because as AI reshapes jobs and workflows, those who engage early will shape what comes next. Become an agent boss Ive seen too many brilliant women opt out because they dont feel technical enough or ready. We saw this pattern during the rise of STEMwhen closing the gap took decades of education and investment. But readiness isnt innate, its built. Say yes to the uncharted projects. Say yes to leading the pilot. Say yes to rethinking how your team works. The most meaningful roles in the AI era wont be assignedtheyll be claimed by those bold enough to step forward. That also means investing in a new kind of skill set. At Microsoft, we talk about becoming agent bossespeople who build, direct, and collaborate with AI agents to amplify their impact. This shift is already underway. In fact, 51% of managers say upskilling for AI will be a core responsibility within five years. Just as we once learned to manage teams, we now need to learn to manage agents. But AI fluency alone isnt enough. If we want to truly change how work feelsnot just how its donewe need to rethink the systems around us. Break the cycle of burnout The pace of work has outgrown the workday. What once fit inside the bounds of a 9-to-5 now spills across time zones, platforms, and personal hours. Our research found that despite 84% of women leaders saying hybrid work improved their experience, 74% still feel they dont have enough time each day to get their work done. This comes as no surprise given that the average employee is interrupted roughly every two minutes275 times a day. Even with gains in flexibility, many are still stuck in cycles of time poverty and busywork. AI offers a way forwardbut only if its paired with structural change. Start with the 80/20 rule: Reclaim time from low-value tasks and reinvest it in what truly moves the business forward. Replace rigid org charts with agile work chartsflexible, outcome-based teams powered by AI to close skill gaps. And empower every employeenot just the technical onesto lead with AI. The magic is in the handoff. For example, AI helps me draft a memo, and an agent tracks the responses and prompts the follow-ups. This frees me to focus on bigger challenges instead of managing my inbox. Because progress doesnt come from the tools aloneit comes from who gets to use them, and how theyre used. Design the future of work The organizations pulling ahead today arent just using AItheyre building with it. We call them Frontier Firms: AI-native companies with digital labor embedded from the start. Theyre leaner, faster, and more adaptive. But what truly sets them apart is how they prioritize people. According to our research, Frontier Firms employees are more likely to report being happier, fulfilled, and able to take on meaningful work. Because real transformation isnt just about technologyits about trust, autonomy, and opportunity. On my own team, weve started making intentional changes: asking whether every meeting is necessary, muting notifications during heads-down time, integrating AI into our workflows, and protecting time for recovery, not just delivery. These small shifts help reset the rhythm of the day and create room for people to thrive. The future of work wont write itself. If we want it to be more equitable, more human, and more inclusive, we have to build it that way. And that starts with more women raising their hands, using their voices, and picking up the pen. Colette Stallbaumer is Microsoft 365 Copilot general manager and WorkLab cofounder.
Category:
E-Commerce
Most ag startups dont fit the venture capital (VC) model. But heres the thingmost companies in most industries dont fit either. VC is where Big Money goes in search of massive bets with massive rewards, typically representing a small part of a diversified portfolio for limited partners. VCs bet billions ($221 billion in 2024 in the U.S.) knowing that theres a 1% chance for any company they invest in to become a unicorn ($1 billion valuation) and that 67% of startups fail to exit or raise follow-on funding, according to CB Insights. Sure, 30% of startups exit via IPO or M&A, but VC goes to the ball to find the 10x return on investment, not to settle for a stepsibling. This topic has been covered ad nauseam lately by agtech VCs and journalists. A recent article from Ag Startup Engine argues that agtech doesnt fit the VC fantasy. The article argues that smaller funds targeting profitable, mid-sized companies pursuing longer-term growth toward $50 million to $200 million exits via M&A are more likely to conserve their capital. And the companies they fund will drive incremental benefits that will make their customers happy. Thats a very reasonable takeaway, and it exists; its called mid-market private equity (PE). But thats not VC, nor does it fulfill VCs purpose of funding high-risk, big ideas that hold the potential to solve farmings biggest problems and change the industrys future. Rather than trying to shoehorn VC into ill-fitted enterprises, the solution is for agtech founders to build Cinderella companies that fit VCs glass slipper model with the potential to deliver magic for the industry and investors. Deja vu all over again You dont need to search much to see that agtech is suffering. But this is a familiar cycle punctuated by rhetoric about how VC doesnt understand ag. This is followed by hope for green shoots that brings to mind a rough morning after: We learned from the mistakes of the past and were going to do things differently. Spoiler alertthe reality is that were not. The same thing that happened in the two previous agtech cycles is happening again: Founders are thinking too small and inside the box. Investors (even more cynical than before) are looking for safe betsthings that dont contradict any of the axioms relayed by the industry (regulatory is long, farmers dont adopt new products, cycles are too long, and everyone inevitably sells to one of the incumbents). If we dont turn this narrative around, the next batch will suffer the same outcome. More capital will flee the space. And the industry will continue churning out incremental products with farmers remaining underserved. Those who dare If we want to break that cycle, its time for founders to swing for the fences and embrace bold visions rooted in contrarian views. If you arent hearing that wont work, it probably isnt daring enough. The sad reality of agtech VC is that risk exists if youre building something small or big, but the reward is only there in the latter. Agtech VC is failing because risk is dominating decision making in the absence of a big upside. And the tendency to suppress and control risk often comes at the expense of accelerating innovation. Three founder behaviors are limiting the upside and creating agtech stepsisters rather than Cinderellas: Creating incremental products: Its safer to lean into an existing market, but its almost always innovation that creates the upside, especially in a mature market. Uber didnt make it easier to hail a taxi, it blew up the market by fundamentally changing how customers managed their transportation. Mimicking the behavior of incumbents: We need innovation in the market approachbusiness model, pricing, marketing, etc.as much as innovation in the product itself. Copying the incumbent playbook might be rationalized by the desire to not reinvent the wheel, but in a world where failure is the norm, its better to innovate every aspect of your business. Building to get bought: Founding a company by planning who you want to sell it to is inherently thinking small, and it drives me bananas. M&A rarely delivers the 10x returns needed to make a case for true VC, so starting with a limited goal makes a poor fit for venture backing. Even worse, by capping the outcome, founders are capping their ambition (without noticing). My company, InnerPlant, was designed from the beginning to swing for the fences, hence fitting the VC model. Weve always known that we were going to learn from how the incumbents disappoint farmers to chart our own path, and weve always aimed beyond M&A. And as for the boldness of the vision, Ive heard to no end that my idea was too hard, too complicated, with too many elements that have to go right. Luckily I found the investors who arent afraid of hard things. The people who said those things werent wrong. But ultimately, VCs are looking at risk versus opportunity; those risks are all still there, but the prize is massiveand that is what venture all about! The future is unknown, and its impossible to predict what will happen when the clock strikes midnight. But founders need to make sure that theyve done everything possible to ensure a big upside so they can fit the glass slipper when the VCs come calling. Shely Aronov is CEO and cofounder of InnerPlant.
Category:
E-Commerce
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