The backdrop for Season 4 is all too familiar to comms professionals: a bristling and “high-growth” start-up is aggressively trying to reposition itself in the market. In this case, Tender, a payment processor historically known for handling adult content and gambling payments, now aspires to become a fintech platform that serves as a “bank killer.”

Quickly into the season, ‘narrative’ becomes the de facto currency. Tender CFO Whitney Halberstram tells his co-founder, “In America, your story starts whenever you begin telling it.” It lands less like dialogue and more as a thesis.

While set against the labyrinth of British aristocracy, the line embodies the new mandate for what it means to run a tech start-up anywhere in the world, illuminating an additional pressure to build in public, brick by brick (or tweet by tweet). What was once shrouded in secrecy and even-keeled press cycles is now conducted in public, with every reply, livestream, and hastily posted Notes app screenshot posted in service of the story. And while almost everyone agrees the old playbook is out, no one can agree on the replacement.

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After all, tech’s obsession with “storytelling” reflects a broader shift: shrunken legacy mastheads and ever-expanding owned distribution channels are creating a media environment low on journalistic scrutiny and high on, well, vibes. You can see it in the rise of creator-led media networks and personality-driven outlets, from Substack newsletter empires to founder-friendly platforms like TBPN, where access, voice, and following often reward narrative momentum over editorial diligence or friction.

In this environment, gatekeepers have multiplied and fragmented. Shaping the story early and in the right places can have an outsized impact before traditional accountability even enters the picture.

It’s for all those reasons that this season captures, with uncomfortable precision, how close communications now sits to the center of power. The stories you tell can matter more than the numbers behind them because the new architecture of influence has decentralized and democratized narrative creation and absorption. And that’s where our job gets heavier.

When narrative becomes real capital (when a single tweet from a founder’s profile can move the market or a headline can buy a company time it may not have earned) communications is less a support function and more a core operating input of both the economic and political order.

Industry understands this. It doesn’t paint comms as a villain or a hero, but as a force that can stabilize or destabilize, depending on whose hands are on the wheel and what incentives are driving the story.

Thomas Jefferson, who envisioned an agrarian democracy as the foundation of American prosperity, famously wrote to George Washington, “Agriculture is our wisest pursuit, because it will in the end contribute most to real wealth, good morals, and happiness.” He saw prosperity, virtue, and happiness as inseparable. Yet today, while America has mastered agricultural production and become one of the world’s largest food exporters, we’ve failed to ensure that our own citizens can share that abundance.

On a human level, it’s unconscionable. On an economic level, it’s catastrophic.

Every year, hunger costs the U.S. economy over $160 billion in avoidable healthcare costs, lost productivity, and diminished potential. Children who are undernourished perform worse academically, reducing future earning potential. Adults facing food insecurity experience higher rates of chronic disease, depression, and workplace absenteeism. These failures compound across generations, economic tiers, and party lines. In any other context, an inefficiency this large would be treated as a national emergency. With hunger, we shrug.

Meanwhile, the affordability gap between wages and grocery prices keeps widening. Food inflation continues to outpace income growth, and the fragility of our federal programs, like SNAP, means millions of Americans live one budget cycle away from losing their most basic lifeline. We can’t keep patching a system that catches people when they fall, but rarely helps them rise. The next evolution of America’s safety net must be a trampoline, one that propels people upward without overdependence on Washington.

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Our nation, founded on the idea of opportunity and earned abundance, is increasingly defined by the daily indignities of scarcity. The question is not whether we possess the resources to end hunger in America (we do), but whether we’ll mobilize them. That requires a clear vision, political courage, and most importantly, bipartisan support.

A systemic solution could restore our economic vitality while also helping renew the American Dream by ensuring every American benefits from our prosperity, rather than merely witnessing it. And American lawmakers can right the ship in months, not years.

Jefferson understood that food sustains more than bodies; it sustains the republic itself. We would do well to remember that.

A third of Gen Z is skipping college before joining the workforce, and opportunities in the internet economy are a major reason why. It’s an inflection point that decades of corporate dread have been building toward.

As the first generation to be raised by the internet, Gen Z didn’t spend our childhoods outside. We spent them online. We exchanged ideas and connected with one another over chatbots long before we learned how to prepare for an interview or apply for a job. We participated in makeshift economies in virtual games long before we opened a bank account or submitted a summer job application.

Our comfort in exploring the internet is why we don’t feel tied to traditional models of work and life that kept people busy for decades, especially as burnout, low wages, and debt continue to dominate headlines post-pandemic. For Gen Z (and the generations to come) inheriting this new reality, the question has evolved from “Where should I apply to college?” to “How can I make money online?”

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Solve your own problem

Solving a problem you’ve experienced creates immediate market foresight. In the pre-Snapchat days, there was no way to send messages without the risk of it being immediately screenshot. Frustrated with our own experiences, my friend-turned-business partner and I launched a messaging platform for self-destructing texts. When Mark Cuban debuted a competitor months later, it was devastating; but it also proved that even a pair of 15-year-olds could match a billionaire’s pulse on the market. Use your experience as initial validation and build quickly from there.

Take shots on net

Starting a business requires doing just that: starting. To give yourself the best possible chance to win, you need to move decisively, with the expectation that not all decisions you make will be the right ones. The good news is that once you’ve identified the problem you aim to solve, there’s never been more resources to learn how to build an online business at every stage, from developing a web app and processing payments to building a customer base, and course correct as needed. You just have to go looking.

Zoom out to zoom in

The world is big; the internet is somehow even bigger. When making money is taking longer than it should, zoom out to see what opportunities lie in the periphery and zoom in on those that can get you closer to your goals. Whether interested in building an online sports betting, reselling, or education empire, there are hundreds of microverticals and millions of potential customers to tap into you’ve likely never thought about. Identify the opportunity, refine your strategy, and execute.

From Clubhouse to Bluesky and now Threads, most new platforms have at some point been designated the vestibule by which social connection and digital community will carry on, only to be thwarted by controversies, content moderation issues, dwindling engagement, and more. Only a month after launch, Threads users are already lamenting over platform burnout.

The hard truth behind the phenomenon? For too long, social media platforms have been operating as if connectivity provides the same fulfillment as human connection. The result is, two decades later, social media’s driven our culture and communal well-being to an unprecedented loneliness epidemic that no platform seems capable of fixing, let alone addressing. It’s time for a hard reset.

In an age where social isolation and loneliness are at an all-time high, perhaps we stop treating connectivity as a substitute and focus on facilitating true, meaningful connections.

· · ·

But social media can’t solve the same issue it feeds (loneliness) without true, exceptional change and a hard reset to place in-person connection at the center.

There have been countless examples of good acts and work forged by social media: of platforms connecting neighbors to one another and resources in times of national need, empowering members of pro-democracy and liberation movements, mobilizing greater civic engagement, and more.

But what all of these examples have in common is the ability to convert digital engagement to community-building IRL (“in real life” for the less online). Or rather, using greater connectivity as a vehicle for building connection and community, not replacing it. We don’t need a wave of social media design that seeks to minimize the impact of these platforms. We now know how powerful they are going to be. Instead, we need a wave of design that imagines a different set of impacts, that move us from myopia to broader perspectives, from isolating and distancing to connection and empathy, from a tribal perspective to the kind of inclusive national and global identities we know we are capable of embracing.

Opening

For a long time, our industry measured success by what we shipped. A new release. A new feature. A go-live date circled on the calendar.

But you don’t buy software for the product. You buy it for what the product makes possible: a faster close, a fuller shelf, a line that keeps running, a customer who gets exactly what they ordered, exactly when they need it.

Quick show of hands: how many of you have an AI pilot running in your business right now? Now keep your hand up if it’s delivering the value you expected. [pause]

That gap between promise and payoff is what we’re here to close.

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Making it concrete

It’s October. You’re a confectionery manufacturer. Someone on your team asks AI a simple question: “Do we have enough bulk candy packs for this week’s Halloween orders?”

Generic AI answers instantly. And confidently. “Yes. 42,000 cases on hand versus 38,000 ordered.”

Sounds great. It’s also wrong. It missed every order placed under the seasonal promo code. It counted stock already allocated to other retailers. And it counted cases that won’t make the retailer’s must-arrive-by date.

None of that is a model problem. The model is smart. It just doesn’t know your business.

Now ask Infor the same question. “9,000 cases short for on-time delivery. Pull Line 3 forward four days to close the gap.”

That’s the right answer and the next action. It applies each retailer’s must-arrive-by dates, knows which cases are already committed, and finds every seasonal promo order. Answering it took three systems: Infor CloudSuite Distribution, Infor Warehouse Management, and the retailer’s own data. That last one isn’t even ours.

If you’d trusted generic AI, you would have lost a lot of money, and made a bunch of kids sad.

How the ontology works

An ontology is simply a map of how your business fits together: what things are called, how they relate, and the rules they follow. The micro ontology knows how each product works. But your business doesn’t stop at one product, so we also built a macro ontology that spans your entire ecosystem, Infor and third-party alike. Micro plus macro. Product plus ecosystem. Together, that’s Infor IQ.

The first piece is our industry process catalogs, which apply the proven best practices and rules of your industry. The second is a knowledge graph that connects each item to the customers who ordered it, the warehouses that hold it, and the plants that make it. So it knows which cases are already committed.

The third piece is a semantic layer. Your systems use different names for the same thing: inventory item, stock item, SKU, material. The semantic layer resolves them into one object the agent can act on. And we’ve done that for every industry we serve.

The origin story

We know a lot of vendors will say they are industry-specific. For us, it’s not a convenient tagline. It’s a promise ten years in the making.

At Infor, we made the choice to be industry-specific when it came time to build our cloud products. We could build one massive ERP platform to serve every industry. Some would call this the obvious choice because it was the least expensive option for us, and gave us access to more markets. But when we really mapped that out, there were tradeoffs that had to be made… It simply wasn’t in the best interest of you, our customers.

So we took a different approach. We built not one but three ERP platforms… each targeting a subset of industries.

From the very start, that industry-specificity has meant we can infuse more capability into the products themselves. But just as important, it means every investment… iteration… and innovation… builds on one another to drive even more value for our customers. On day one, day one-thousand, and beyond.

Making it concrete

Let’s look together at a simple example: invoice processing across three different industries. You may be thinking: how complicated can it be?

In industrial manufacturing, you have to grapple with PO matching. Compare that to food and beverage manufacturers, who are dealing with a lot of variability. For example, a truckload of potatoes might be one weight when they leave the farm, and another when they arrive at their destination.

Next, consider fashion and retail. Think of all the different fabrics, buttons, and textiles that go into making a single piece of clothing. And that’s just one piece. For one season.

And this is just one process. One of the thousands that make a business tick.

Executive summary

AI investment is surging, but organizations need to close the post-adoption gap or risk leaving ROI unrealized

Organizations everywhere are rushing to adopt artificial intelligence (AI) through chatbots, agents, pilots, and more. Investment is surging, but market data shows value still lags behind the hype.

As the potential becomes even more apparent, every organization is under pressure to become an agentic enterprise: an organization where AI agents and people work as one coordinated system, executing tasks, orchestrating workflows, and making decisions across the business, all under human oversight.

Yet there’s a critical obstacle in the way: the post-adoption gap that comes after initial AI deployment, where systems can quickly break under pressure and early wins stall before they ever reach enterprise scale.

Data visual treatment

68% of surveyed leaders say off-the-shelf AI doesn’t fit the needs of their business. 88% say predictable pricing is important, yet 71% do not have a comprehensive understanding of long-term costs.

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More authority, higher stakes

As humans transfer more authority to AI agents, so does the expectation that agents can handle not just specific tasks, but entire complex workflows end-to-end. Whether that expectation is met comes down to how well the systems handling those end-to-end workflows are built.

Handed to a well-orchestrated system, where agents share context, data, and reasoning models, trust compounds into efficiency and value. Handed to a fragmented one, where agents work in isolation, with disparate data and model logic, costs compound, and risks go unnoticed until they’re expensive to unwind.

If these survey findings hold, agents will continue to gain authority. But orchestration will determine whether that authority shows up on the balance sheet as value or as a cost.

For Gen Z, seeing their friends in their feeds is believing.

Gen Z decision-making runs on a peer-to-platform loop. They want to see their friends using a brand’s products, and simultaneously engage with the brand’s content. 85.9% of Gen Z respondents say friends using a product makes it feel more culturally relevant, versus 68.4% of the general population. If a brand isn’t being modeled by their friends or their feeds, it remains outside the Gen Z zeitgeist.

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Show time and sincerity unite every generation.

Across all the generational differences in what makes a brand feel relevant, two things hold true for everyone.

First, TV and film is the one space where every generation — and every income level — stays locked in, with engagement reaching 65% across cohorts. It’s also where different generations are most likely to watch the same thing at the same time: prestige shows, live events, and big movies still bring Gen Z and Boomers together, sometimes on the same couch. For brands, that means one placement can reach all of them at once.

Second, authenticity is the easiest of 11 relevance factors to agree on across generations. Brands like Carhartt and New Balance show gaps of just 1.8 and 2.8 points between how Gen Z and Boomers rate their authenticity — nearly identical across a 60-year age span. For the brands that get it right, authenticity is a foundation for relevance in every other area.

For brands that want to connect with the widest audience, the answer is straightforward: show up on screen, and be genuine first.

Headline

Introducing the Agentic Enterprise

How industry expertise becomes action at scale.

Enterprise solutions are only as valuable as they are useful, trustworthy, and fit into both your operations and the world that surrounds it: the processes, the pressures, the people, and the time constraints.

Moving from embedded intelligence to coordinated, agentic workflows unlocks that value.

Infor calls this the Agentic Enterprise: an operating model where industry-specific AI agents operate across systems, orchestrated by a central authority layer, to turn intelligence into precise business outcomes at machine speed.

What does this look like in practice?

Complexity fades into the background. Agents trained on decades of industry knowledge and proven best practices can handle complexity and act on your behalf.

Precise value is unlocked, faster. Because industry meaning is built in, every AI recommendation and outcome reflects the actual logic of your business: your terminology, your margins, your compliance requirements, your customer commitments.

Your business moves forward, with trust built in. Every action, whether initiated by a person or an agent, is governed, auditable, and operating within defined business constraints.

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Data visual treatment

Infor’s solutions reduce implementation timelines by up to six months and 37% lower integration costs. Gellert Global, the largest specialty importer in North America, with over 6,000 SKUs, reduced integration timelines from years to just three months to scale its acquisition strategy.

Section header

After go-live, maximize your investment and continuously realize value with Agentic AI. Go-live is just the starting line. With Infor’s Agentic AI capabilities, what used to require human stitching across departments, data sources, and third-party tools now runs as end-to-end, governed workflows, freeing teams to focus on the decisions only they can make.