As 2026 begins, many organizations are launching AI transformation initiatives. The new year brings with it fresh budgets, renewed strategic focus, and mounting pressure to capture value from artificial intelligence. Yet studies consistently show that most AI projects fail to generate meaningful returns. Companies pour resources into promising experiments that never scale, accumulate tools that are never integrated, and watch initial enthusiasm curdle into skepticism.
What separates organizations that create lasting value from those that dont is rarely the technology to which they have access. Instead, the critical secret sauce lies in having a systematic, rigorous, and repeatable approach that allows the leadership team to move from the identification of opportunities to operational deployment.
This article offers a practical playbook for that journey, using the illustrative example of a midsize manufacturing firm (Aurora Windows). While the playbook itself distills learnings gained from large, technically sophisticated businesses in sectors such as defense and finance, our example shows how these lessons can be applied even in late-adopting companies with limited resources. At present, there are few examples of systematic end-to-end AI innovation pipelines that have been deployed successfully in the real world, so our example can only be illustrative. Nevertheless, forward-looking companies are already beginning their journeys along this path and evidence from decades of organizational and digital transformation efforts allow us to model what success will ultimately look like.
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I will be using this playbook in my upcoming guest lecture for IMD Business School’s AI strategy and implementation executive program, delivered in collaboration with Misiek Piskorski, dean of executive education at IMD, and Amit Joshi, codirector of the program. IMD is a world-leading business school, ranked No. 1 globally in custom executive education by the Financial Times (2025), renowned for transforming rigorous research into actionable leadership results.
An Illustrative Example: Aurora Windows
Aurora Windows is a 35-year-old, second-generation manufacturing company that designs and produces doors, windows, and architectural glass for commercial and residential building projects. With roughly 220 employees across one main plant and two regional distribution hubs, it sits in the classic too big to be small, too small to be big SME band: large enough to feel pressure from global competitors and construction giants, but without a dedicated transformation department or a large consulting budget. Over the next five years, the leadership team aims to position Aurora as the go-to innovation partner for sustainable, smart building projects by becoming a fully AI-driven business.
The Innovation Pipeline
To succeed in its goals, Aurora needs to take a disciplined approach to AI enterprise transformation that treats the innovation process as a continuous structured pipeline with clear stages. Projects flow from initial ideation into a rigorous assessment phase and on to operational deploymenta narrowing funnel that sees many ideas entering but only the strongest and most strategically aligned reaching production.
Firms in some sectorssuch as tech and pharmaceutical companieshave long relied on continuous product development pipelines that systematically advance projects from abstract ideas to market-ready products. In the AI age, every organization needs to adopt this kind of systematic approach to innovation. But this is more than just a new product development pipeline: Innovation projects must be aligned with the broader organizational culture and processes within which they will be embedded.
Step 1: Current-State AssessmentEstablishing Your Baseline
Before Aurora can begin managing an innovation pipeline, the leadership team needs to understand where the company currently stands. They conduct a baseline assessment across three dimensions:
Organizational purpose and strategic clarity
Auroras executive team revisits its core mission: creating high-performing, sustainable door, window, and glass solutions that make buildings safer, more comfortable, and more energy efficient. The team articulates three specific five-year goals:
40% revenue growth without proportional headcount increases
Margin protection despite volatile input costs
Positioning as the go-to AI-driven innovation partner.
This clarity becomes the North Star for evaluating every AI initiative.
Knowledge baseline
The team then assesses the companys current AI literacy. At present, there is a scattering of expertise across departments, with individual enthusiasts driving the current pilot programs. AI knowledge in the leadership team is limited and most of the businesss staff are unfamiliar with basic machine learning concepts.
Risk appetite
Aurora is a family business that has survived by not taking reckless bets. But the market is shifting. Competitors are beginning to offer AI-enhanced design services and predictive maintenance. The leadership team articulates a balanced stance toward risk: Aurora needs to advance more rapidly than they would normally be inclined to move, but with guardrails in place to protect the brands hard-won reputation.
This assessment reveals uncomfortable truths. Aurora has enthusiasm for AI transformation but no shared knowledge base or language for discussing AI, and no accepted criteria for assessing the value of pilot projects. The leadership team has ambition but there is currently no defined path to move projects from the pilot phase to company-wide operation. Most importantly, there is no mechanism for deciding what to do next.
Step 2: OpportunitiesPopulating the Innovation Pipeline
Auroras leadership now launches a structured ideation process to identify projects that are explicitly aligned with the companys strategic goals. Rather than asking What can we do with AI? cross-functional teams ask What poblems prevent us from achieving our strategic goals, and can AI help us solve them?
The teams quickly generate two dozen initial ideas spanning multiple AI types: analytical AI for process optimization, workflow automation to reduce manual tasks, generative AI for design acceleration, and even agentic AI systems operating semiautonomously within defined parameters.
Each idea receives a rapid initial assessment using five criteria scored 1 to 10:
Priority: How urgently does this support our core goals?
Risk: Whats the potential downside if this fails after deployment?
Value: Whats the likely financial or strategic return?
Cost: What investment is required to reach production?
Difficulty: How challenging will implementation and adoption be?
When scored and ranked, clear patterns emerge. Several high-scoring opportunities cluster around production efficiencyusing computer vision for defect detection, AI-driven equipment maintenance prediction, and automated quality documentation. A number of initiatives focusing on design acceleration and customer experience receive medium scores. Several moon shot projects that were initially very popular with senior leaders receive low scores because they are technically difficult, expensive, and come with significant risks, despite their high potential payoff.
This process also surfaces important dependencies. A design acceleration project that has many supporters would require clean CAD libraries and standardized templateswork that hasnt started yet. Similarly, a maintenance prediction system needs sensor data that is not yet available but that would be generated if one of the quality inspection projects goes ahead.
The ideation exercise produces more than a ranked list of ideas. It creates a common vocabulary for discussing AI opportunities at the same time as revealing capability gaps and building consensus around which directions make strategic sense. Of Auroras 24 ideas, 6 scored highly enough to warrant further detailed assessment. The rest remain in the backlognot definitively rejected, but requiring either new capabilities or a shift in strategic priority to make them viable.
Step 3: AssessmentEnterprise Architecture Analysis and Fit
The six projects that ranked highest in the initial screening now enter detailed assessment. Auroras leadership team first maps the organizations Strategic Enterprise Architecture (SEA) and then assesses each projects degree of fit across four dimensions:
Purpose and Strategic Intent
Does this project directly advance Auroras three strategic goals with clear, measurable outcomes?
People and Culture
Are leadership and staff ready for the changes the project involves?
Processes and Governance
Can the initiative integrate with current processes and operating models?
Technology Architecture and Data
Is the initiative feasible using existing or available systems?
The results are sobering. Of the six projects under assessment, only three demonstrate clear alignment across all four SEA dimensions. Two of the others could become viable with specific capability-building work.
The SEA analysis also reveals positive insights. The quality inspection camera project will generate structured defect data that several other proposed projects can use. By recognizing this dependency, Aurora can sequence projects to build on this foundation.
Step 4: OperationalizationFrom Experimentation to Production
The three projects that passed detailed assessment now undergo active experimentation. Aurora structures these experiments as learning journeys, not just technical validations. The visual quality inspection project runs bounded pilots on specific production lines. The AI-assisted design tools are tested with a small R&D team before broader rollout. The data infrastructure project proceeds in phases, upgrading one integration at a time while minimizing disruption.
After six months of experimentation, the newly developed quality inspection tool passes all tests and moves to production. The data infrastructure project shows promise but needs another quarter of refinementit remains in experimentation. After a promising start, the AI-assisted design tools run into a technical wall. With no clear path forward, the project is paused until a technical solution is identified.
Systems that reach production require ongoing monitoring, cost tracking, and impact measurement. Aurora establishes guardrails to prevent misuse and implements continuous monitoring to catch issues before they become problems.
Sustaining the Pipeline
Auroras innovation pipeline is a long-term, repeatable system that provides the engine for continuous AI transformation. But to deliver its value, it must be carefully tended. The leadership team establishes a quarterly review process with three goals:
Project health checks
Are experimental projects meeting milestones? Are production systems delivering expected value? Do any initiatives need intervention, resources, or retirement?
Pipeline rebalancing
As projects advance, move into production, or are killed, the pipeline needs replenishment. The leadership team takes a view across the entire pipeline to ensure that the right mix of projects is moving through, balanced across time horizons, risk levels, and strategic targets.
Strategic recalibration
Markets, technologies, and organizational priorities shift. Quarterly reviews explicitly ask: Do our scoring criteria still reflect strategy? Are new capabilities or partnerships available? Have competitors made moves that change our priorities?
This operating rhythm transforms Auroras relationship with AI. Instead of episodic enthusiasm followed by disappointment when pilots dont scale, the leadership team has a sustainable engine for continuous improvement. Each quarter brings visible progresssome quick wins, some foundation building, some ambitious bets advancing.
Within 18 months, Auroras transformation becomes tangible. The company now has three AI systems in production (quality inspection across all lines, automated quality documentation, and a new LLM-powered customer portal). The projects in experimentation and assessment build on these initial experiences and include initiatives that have become viable thanks to the technical capacity, skills, and processes developed while working on the initial round of projects. By avoiding wasteful efforts to develop a series of unconnected pilots with no clear strategic value, Aurora has built a foundation of success that is propelling it past its competitors.
Conclusion: The Management System Behind the Pipeline
Auroras story highlights a fundamental truth about AI transformation: Technology is rarely the constraint. Most companies can access impressive AI tools. What they lack are the management systems needed to deploy those tools strategically, build repeatable capabilities, and create sustained value.
An innovation pipeline like the one in our example does not run itself. It requires systems and structures that creat both horizontal and vertical collaborationlinking the C-suite to project teams and linking project teams to the rest of the organization. Without these connections, even the best-designed pipelines will stall.
Cultural change is often framed as a precondition for AI transformation. But culture doesnt shift as a result of exhortation alone. It is shaped and steered by the processes, review rhythms, and governance structures that determine how decisions get made and how work flows through the organization. Quarterly reviews, cross-functional assessment teams, and clear advancement criteria arent bureaucratic overhead. They are the mechanisms through which a culture of disciplined innovation takes root.
The companies that succeed with AI wont be those with the most ambitious pilots or the earliest adoption of new tools. They will be those that build the management systems that are needed to move systematically from opportunity to assessment to operationand to sustain that movement over time.
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When a 7.7-magnitude earthquake hit Myanmar last year, roads buckled and thousands of buildings collapsed. But a group of small, ultra-low-cost homes made from bamboo survived without any damage.
Finished just days before the quake, the houses are emergency shelters for some of the millions of people displaced by Myanmars ongoing civil war. Myanmar-based architecture studio Blue Temple worked with its spinoff construction company Housing Now to make the simple prefab homes as low-cost as possible while still able to withstand natural disasters.
We built them for the price of a smartphoneabout $1,000 U.S. dollars per house, says architect and Blue Temple founder Raphaël Ascoli.
[Photo: Raphaël Ascoli]
Engineering bamboo for earthquake resilience
Bamboo has a long history as a construction material in the country, but the team saw an opportunity to innovate with it. Ascoli, who has been working in Myanmar for the last decade, partnered with a local bamboo carpenter on the concept.
[Photo: Raphaël Ascoli]
The material is already cheaper to use than wood, concrete, or steel. But the architecture studio helped cut costs further by using a thin, low-cost species of bamboounlike the large species typically used in constructionand bundling it together to make it stiff and strong.
The construction company builds beams from the bamboo and then puts them together in structural frames that we can just assemble like an Ikea kit in less than a week, says Ascoli. Because of the organic natural of the bamboo that we weave together into the frames, it gives the house a bit of flexibility. Instead of being very stiff and brittle like concrete, it can move a little bit.
[Photo: Aung Htay Hlaing]
Any bamboo structure has some advantages in earthquakes because of its light weight and flexibility, but the company found ways to boost that performance. We built a lot of prototypes and then pulled on them until the breaking point, Ascoli says. You can evaluate the maximum pressure that can be put on the house before failing. They made tweaks to each joint to make the buildings stronger and more weatherproof.
The massive earthquake was a real-life proof of concept, says Ascoli. The homes, in a camp for displaced people, were less than 10 miles from the epicenter of the quake, but none of them needed repairs.
[Photo: Aung Htay Hlaing]
A DIY path to scaling shelter without NGOs
The company has been building homes for displaced people since Myanmars coup in 2021. While the design can be flexible, its typically a simple room that residents can divide for living and sleeping; camps have separate shared bathrooms and kitchens.
[Photo: Aung Htay Hlaing]
So far, the work has happened at a relatively small scale. The team is small, and funding from NGOswhich was limited to begin withhas started to disappear. When the Trump administration shut down USAID, that had massive consequences on the humanitarian response in Myanmar, says Ascoli. A lot of NGOs are now closing down and unable to continue operating. Other countries have also cut funding. Theres also a shortage of construction labor because of the war.
[Photo: Raphaël Ascoli]
To keep going, the team is experimenting with new approaches. If we want to scale, we have to be radical, he says. The latest project, developed over the last 18 months, is a DIY construction manual that helps citizens incorporate some of the design teams techniques to optimize bamboo construction as they build homes themselves.
The humanitarian sector is kind of failing at the moment because its relying on unreliable sources of funding, and its an archaic system, says Ascoli. Were basically trying to test out if there is an alternative to traditional humanitarian response, and trying to find what can be the post-NGO humanitarian response programs that will replace the old systems.
Trust used to be the benefit of the doubt. Now it is the battle to be won.
Recently, I asked a CEO client why she didnt want to speak on a panel her team had been invited to. Her answer? Id rather the company speak for itself. I dont want to make it about me. That hesitation is common. Many leaders assume visibility is self-serving. But today, staying behind the scenes isnt humility. It’s a risk.
When nearly 70% of people believe business leaders intentionally mislead the public, credibility and trust, not marketing, has become the new currency. We are leading in an era when silence is interpreted as indifference and visibility is mistaken for vanity. That tension has paralyzed many executives who want to do the right thing but do not want to appear self-promotional.
I have spent more than a decade helping CEOs, founders, and entrepreneurs turn visibility into a strategy rather than a stunt. The most successful ones have mastered five internal shifts that rebuild trust from the inside out. None of them requires a massive budget. All of them require courage.
1. Step out from behind your business and stand beside it
Many leaders still assume that the company should speak for them. That used to work when audiences trusted corporations implicitly. Today, people look for the human behind the logo. According to Edelmans 2025 Trust Barometer, business remains the most trusted institution, yet that trust is now tied directly to individual leaders.
Visibility is not about ego. It is about accountability. When you put your name to your mission, it tells employees and customers that you believe enough in the work to represent it personally.
Start small. Write one LinkedIn post each week that connects your leadership values to what your team is building. Share a story from the trenches, a tough call you made, a lesson you learned, or even a mistake that clarified your priorities. Authentic leaders do not curate perfection. They clarify purpose. The goal is to stand alongside your company, not in front of it or hiding behind it.
2. Define your ‘Influence ID’ before you define your strategy
In every workshop I run, I ask leaders one question: Who are you in addition to being a CEO or founder?
That question is often followed by a long pause. Most can rattle off quarterly goals faster than personal convictions. Yet your ability to articulate who you are shapes whether people trust what you sell.
I call this your Influence ID. It is the unique mix of values, experiences, and strengths that differentiates you from every other leader in your industry. It is not a tagline. It is a compass.
Try this exercise. Write down eight aspects of your brand wheel: skills, stories, causes, or passions that make you who you are. Notice where they overlap. Maybe your financial discipline fuels your advocacy for small business transparency. Maybe your love of coaching kids sports mirrors how you lead teams. Those intersections reveal your authentic narrative.
When you know your Influence ID, every decision, from interviews to investor decks, aligns naturally. You stop performing a brand and start embodying one.
3. Turn your visibility into a trust engine
The loudest leaders do not necessarily win. The most trusted ones do.
The 2025 Edelman Trust Barometer found that 61% of people believe both business and government are failing people like them. In that environment, communication has to shift from promotion to education. The leaders earning trust today act less like advertisers and more like teachers.
Start by reframing every outward communication with one question: What value does this give my audience? If you are announcing a product, explain the problem it solves. If you are celebrating a milestone, share the lesson that others can apply.
Use the three-to-one rule I teach executives: three insights or resources for every one piece of company or product promotion. This ratio forces you to build goodwill before you ever ask for attention. Over time, consistency compounds into credibility. People stop seeing you as a marketer and start seeing you as a mentor. That is the moment visibility becomes trust.
4. Treat thought leadership like a business asset, not a marketing hobby
For most organizations, the real decision-makers are not the ones sitting in sales meetings. They are the unseen influencers in legal, finance, or operations who quietly determine whether a deal moves forward. Edelman and LinkedIns 2025 B2B Thought Leadership Impact Report calls them hidden buyers. They read deeply, think critically, and use high-quality thought leadership to decide whom to trust.
That means every article, podcast or op-ed you publish is more than content. It is collateral in the trust economy.
Audit your digital presence the way you would a financial statement. Ask yourself:
Is your expertise visible where those hidden buyers are researching?
Do your insights challenge assumptions rather than echo trends?
Does your tone invite dialogue instead of demand attention?
Pick one platform, such as your newsletter or LinkedIn. Commit to showing up consistently for 90 days. Measure success not by likes but by opportunities: invitations, partnerships, and client inquiries. Those are the new trust metrics.
5. Build a brand that outlasts your business
Many founders sell their companies and then realize they sold their voice along with them. I have watched brilliant entrepreneurs exit successfully only to feel an unexpected emptiness. Their entire network, data, and even audience list transferred with the deal.
Your business is an asset. You are the equity.
Start protecting that equity now. Maintain an email list, personal website, or professional profile that belongs to you, not just your company. Capture the lessons you are learning in real time through a blog, internal newsletter, or short video updates, and keep those archives. When the next chapter comes, you will have a built-in platform ready to launch whatever comes next.
Think of it the way Sara Blakely did when she sold a majority stake in Spanx but announced it from her personal Instagram rather than a press release. Her audience followed her, which meant every future venture started with a foundation of trust already built.
The modern trust equation
You do not need millions of followers to be influential. You need the right 500 people who are in your target audience and believe you stand for something real. You want to create raving fans out of those 500 people.
Leadership visibility is not about spotlighting yourself. It is about directing attention toward a mission that matters. The skeptics will always ask, Cant CEOs just lead quietly? They can, but quiet leadership is invisible leadership, and invisible leadership no longer earns trust.
So stand beside your business. Define your Influence ID. Teach, not preach. Publish with purpose. Build a reputation sturdy enoughto outlast any logo.
In the age of skepticism, the most powerful marketing strategy remaining is the truth spoken by a leader who is willing to show up and stand by it.
Adapted from The Strategic Business Influencer: Building a Brand with a Small Budget. Copyright 2025 by Paige Velasquez Budde. Available from Matt Holt, an imprint of BenBella Books, Inc.
Every organization believes it’s in the productivity business. Every executive thinks faster, longer, more densely packed meetings equal better results. They’re wrong.
The meetings that actually workthe ones where breakthroughs happen and teams leave energized rather than depletedoperate on a completely different logic. They’re designed around how human brains actually function, not how we wish they would.
By helping organizations transform their cultures through my Move. Think. Rest. (MTR) framework, I’ve watched the same pattern emerge: Companies spend millions on the latest collaboration software and meeting tech, then squander the opportunity by applying the same exhausting, back-to-back scheduling that got them nowhere in the first place.
Here’s what needs to change.
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Rhythm, Not Relentlessness
We should stop treating breaks as a tax on productivity and instead understand that breaks are an investment in our productivity. Most conference agendas are built on the assumption that more content equals more value. It’s an assumption that breaks the human brain.
Our cognitive architecture doesn’t work in endless marathons. It works in cycles. This is why the best meetings I’ve redesigned follow a simple principle: Build MTR directly into your schedule.
Start with Movement by designand I don’t mean “take a walking break.” I mean fundamentally restructuring how your sessions happen. Convert at least one daily brainstorming session into a walking meeting. The research is clear: When bodies move, ideas flow. The Navy figured this out decades ago with standing meetings. They’re more effective and efficient because motion isn’t a distraction from thinking, it’s a catalyst for it.
For the Think dimension, protect what I call “suspended time.” Back-to-back sessions aren’t intensive, they’re destructive. Replace that model with 75- to 90-minute deep-dive blocks followed by genuine transition time. Before bringing insights to a large group, let people first reflect individually, then discuss in pairs. This honors how people actually process: We need space to diverge before we can meaningfully converge.
And Rest is nonnegotiable, which means we should stop treating breaks like their mechanical pit stops, as if theyre stealing time from productivity. Build in 15-minute microbreaks between sessions: intentional pauses where people actually step away, stretch, move outside, daydream. Research shows that even 10 minutes of genuine rest sustains performance and enhances well-being. Daydreaming helps with generative, divergent thinking. And a midday break that’s longer than the time it takes to eat lunch at your desk isn’t a luxury. It’s the infrastructure that makes everything else work.
Redesign Your Agenda Language
Words shape experience. When you say break, you signal that time is lost. When you say integration time or reflection pause, you signal that this moment is essential to how you do your best thinking.
This matters more than you’d think.
Here’s what belongs on your ideal meeting agenda: sessions scheduled during people’s natural peak cognitive times (usually mid-to-late morning), unconference elements where participants help build the agenda in real time, movement infrastructure built into the physical environment, and explicitly named transition time. What doesn’t belong: purely informational sessions that could be prerecorded, expectations that people perform at full capacity from 8 a.m. to 6 p.m. straight, and the assumption that measuring success means measuring how much you packed in.
The Changes That Actually Move the Needle
The highest-impact redesigns don’t require massive budgets. They require a different mindset.
Implement meeting-free blocks. Designate specific timeperhaps the first three hours of a multiday conference, or entire afternoonsas true meeting moratoriums. Not break time. Deep work time. People use it for reflection, processing, or the spontaneous conversations that often yield the most valuable insights. This single change transforms an event from overwhelming to generative.
Build movement infrastructure. Provide mapped walking routes with estimated times. Create outdoor spaces with seating for breakout sessions. Install standing-meeting areas with whiteboards. When movement is built into the physical environment, it becomes the default rather than something people have to engineer.
Create rituals of rest. Start each day with 10 minutes of optional guided stretching or meditation. End each day with a brief reflection session. Designate quiet zones for afternoon restoration. When rest is ritualized, it shifts the entire culture.
Measure differently. Stop asking whether you covered all the content. Start asking: What unexpected insights emerged? What new connections formed? How energized do people feel when they leave? This shift in metrics naturally leads to better design choices.
The Competitive Advantage of Flourishing
Here’s what most leaders miss: The meeting redesign isn’t (just) about being nice to people. It’s about being strategic.
When you move from productivity theater to cultivation-centered design, you unlock something more valuable than efficiency. You unlock the kind of thinking that emerges only when people have genuinely processed information, made authentic connections, and restored their cognitive resources. You create conditions where innovation doesn’t come from forcing harder, it comes from creating the rhythmic space where human flourishing and breakthrough thinking naturally intersect.
The organizations that understand that meeting are systems, not schedules, will find themselves with teams that are more innovative, more engaged, and, frankly, more loyal.
Stop stacking. Start designing.
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A few of the neatest gadgets at the Consumer Electronics Show (CES) 2026 werent anywhere near the Las Vegas Convention Center trade show venue.
Instead, they were sitting on a table at The Venetian Resort’s food court, at least on Monday when Core Devices founder Eric Migicovsky was holding press meetings. He had a couple of quirky Pebble smartwatches to show off, with lo-fi e-paper screens in round and rectangular forms, and he was wearing an early version of the Pebble Index, a smart ring whose main job is capturing voice notes. (He moved to a booth in the bowels of the Venetian expo when CES officially got underway.)
Unlike a lot of exhibitors, Migicovsky isnt promising anything revolutionary, but he also made clear that Cores mission has expanded. Beyond just making smartwatches, he now sees the company as a purveyor of fun but indispensable gadgets. The Pebble Index is just the start.
Core Devices is building the gadgets we want, (because) no one else is, he says.
Three watches and a smart ring
Its now been about nine years since Pebble shut down, selling its assets to Fitbit after the Apple Watch sucked out the oxygen for smartwatch startups. Maybe Pebbles fate was unavoidable, but Migicovsky also regrets overextending into areas he wasnt passionate about, like fitness tracking. (Im not a Whoop guy, he says.)
Core Devices is a chance to start fresh. After spending three years as a Y Combinator partner, and then selling his messaging startup Beeper to Automattic (reportedly for $125 million), Migicovsky has no desire to go the usual startup route again. When Google agreed to open-source the original Pebble operating system last year, he put up the R&D money for a new batch of watches, then started taking preorders.
With the new Pebble watches, the core appeal is the same as the originals: Geeky watch faces, reliable push button controls, e-paper screens for long battery life, hackability. For Core Devices’ first new watch, the Pebble 2 Duo, the hardware is also similar, as Migicovsky found a supplier with some original Pebble 2 components and repurposed them into 8,000 new watches that shipped late last year.
The next batch of Pebbles is more like what the original company mightve built if it survived for longer. The $225 Pebble Time 2 looks like a standard rectangular smartwatch, except it lasts for a month between charges, while the $199 Pebble Round 2 ditches heart rate monitoring for a slim design and two weeks of battery life. Both have larger screens and much narrower bezels than any of Pebbles original watches.
As for the $99 Pebble Index 01 ring, Migicovsky says the idea came from struggling to remember things and wanting to record them in way that became muscle memory. Talking into the ring while holding its clickable button records a voice note, which a companion app transcribes into text. A double-click allows for programmable actions such as smart home controls or AI queries (whose answers, for instance, could appear on a Pebble). A Pebble app with similar functionality is coming, but the point of the ring is that you only need one free thumb to use it.
Meanwhile, Migicovsky is cutting out all the things he hated about making hardware before. He raises money for the watches through preorders instead of investors, sells them through Cores website instead of dealing with retailers, and doesnt bother with sales forecasting.
The resulting sales have been modest25,000 Pebble Time 2 preorders, 7,000 more for the Round, 8,000 for the now-sold-out Pebble 2 Duobut the company has far exceeded its minimums for what Migicovsky considers viable. That means Core Devices can keep making new gadgets.
We decided this go-round that well just do the things that are fun, he says.
Beyond the watch
Among longtime Pebble fans, the Index ring has been contentious, in large part because it’s not designed to last. Its internal battery isn’t rechargeable or replaceable, and after 12 to 15 hours of recording time, it’ll simply stop working. (Migicovsky estimates a two-year lifespan for someone who records 10 to 20 thoughts per day.) Core Devices will offer to recycle the metal, but it’ll throw the electronics away.
Migicovsky says the single-use battery was necessary for an attractive design with water resistance, and he likes the idea of never having to take the ring off, even in the shower. But because the original Pebble watches have endured for so longa decade later, thousands of people still use theirsthe Index’s disposable nature feels incongruous even if Migicovsky downplays it.
I would say that most devices are made to be thrown away, and thats the secret of the industry that nobody ever talks about, he says.
The Index also just indicates that Core Devices is more than a smartwatch company now. While the original goal was to scratch one specific itch, Migicovsky now says he has “lots more” ideas for new products.
There will be prerequisites: Whatever Core Devices makes can’t already exist, must have low R&D costs, and should be possible to build with a small team. (The company currently employs five people, all on the software side besides Migicovsky himself.) Its products will have to solve everyday problems, even if they’re niche ones.
Still, the company has more things to figure out first. While the Index uses on-device speech-to-text for voice notes, it’s unclear how it’ll cover the cost of using AI to process custom commands, or for its optional Wispr Flow-powered transcriptions. Migicovsky doesn’t love the idea of subscriptions but isn’t sure about alternatives. Employing a team obviously has ongoing costs as well, which means Core Devices will need to expand from its tiny audience, find recurring revenue streams, or keep releasing new things.
But even as it expands, Core Devices is keeping its ambitions in check, which at a venue like CES can be pretty refreshing. Were not trying to invent some new computing category,” Migicovsky says. “Were not trying to take over the world.
Although there is no shortage of AI enthusiasts, the general public remains uneasy about artificial intelligence. Two concerns dominate the conversation, both amplified by popular and business media. The first is AIs capacity to automate work, fueling widespread FOBO, or fear of becoming obsolete. The second is AIs tendency to reproduce or even exacerbate human bias.
On the first, the evidence remains mixed. The clearest signal so far is not the wholesale replacement of jobs, but the automation of tasks and skills within jobs. Most workers are less likely to lose their roles outright than to be forced to rethink what they do at work and where they add value. In that sense, AI is less an executioner than a pressure test on human contribution. As we have previously noted, AI is exposing the BS economy, in the sense of automating low-value activity and commoditizing whats not relevant.
On the second, however, concerns feel more visceral, since theres clear evidence of AI amplifying or at least perpetuating human biases. Indeed, algorithms replicate the loudest and most common outcomes. Tools trained on historical hiring and promotion data mirror the demographic preferences of past decision-makersoverlooking qualified candidates and harming both those individuals and the organizations that end up missing out on better talent. Large language models producing outputs that disadvantage marginalized users because of skewed training data. Add to this the political and moral assumptions embedded, often unintentionally, in AI systems, and its easy to conclude that AI is simply a faster, colder version of human prejudice.
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To be sure, AI will never be bias-free. And yet it can still be less biased than humans (okay, its a low bar). Importantly, under the right conditions, it can make things a lot better.
Humans are biased, but thats not a bug, its a feature. Its a consequence of cognitive shortcuts that evolved for speed and survival. But survival is knee-jerk, and often optimizes for the immediateand shortchanges the long-term success that comes from thoughtfulness and fairness. Nobel Prize winner Daniel Kahneman showed us how quick decisions are often suboptimal, yet we rely on those quick, intuitive decisions frequently, and even more frequently when we are under stress and time pressure.
Yet one of the great strengths of humanity is that we are also capable of reflection and correction. And AI is in some ways uniquely suited to help counteract predictable distortions that have plagued humanity for centuries.
Consider six ways this is already beginning to happen.
1. AI can help us better understand others
AI is now embedded in many of the platforms we use to communicate at work. Increasingly, it can analyze patterns in language, tone, and behavior to infer emotional states, intentions, or levels of engagement. Tools like Textio help us get out of our own way by flagging language thats not aligned to our goals. These systems are far from perfect, but they dont need to be. They simply need to outperform the average human in situations where human judgment is weakest.
Research on emotional intelligence shows that people are generally better at reading members of their own group than outsiders. Cultural distance, unfamiliar communication styles, and implicit stereotypes distort perception.
AI systems trained on data from different cultures and groups can sometimes decode signals more consistently than humans navigating unfamiliar social terrain. Theres evidence that using technologies like VR to experience others realities can build lasting empathy. Used responsibly, these kinds of augmentation can support empathy rather than replace it, helping people pause before misinterpreting disagreement as hostility or silence as disengagement.
2. AI can force us to confront alternative viewpoints
One of the ironies of AI criticism is that we often accuse systems of bias as a way of deflecting attention from our own. When people complain that generative AI is politically or ideologically slanted, they are usually revealing where they themselves stand.
Properly designed, AI can be used to surface competing perspectives rather than reinforce echo chambers. Whats more, AI can do this by framing arguments and evidence in ways that make them easier to understand and accept without triggering judgment or combativeness.
For example, leaders can ask AI to articulate the strongest possible case against their preferred strategy, or to rewrite a proposal from the perspective of different stakeholders. In conflict resolution, AI can summarize disagreements in neutral language, stripping away emotional triggers while preserving substance.
This doesnt make AI objective, but it can make us less lazy. By lowering the cognitive and emotional cost of perspective taking, AI can help counteract confirmation bias, one of the most pervasive and damaging distortions in organizational life.
3. AI can improve meritocracy in hiring and promotion
Few domains are as saturated with bias as talent decisions. Decades of research show that human intuition performs poorly when predicting job performance, yet confidence in gut feeling remains stubbornly high.
When trained on clean data and validated against real outcomes, AI consistently outperforms unstructured human judgment for job decisions. This is not just because algorithms can process more information, but because they can ignore information humans struggle to disregard. Demographic cues, accents, schools, and social similarity exert a powerful pull on human decisin-makers even when they believe theyre being fair.
Well-designed AI systems can also be updated as job requirements evolve, allowing them to unlearn outdated assumptions. Humans, by contrast, often cling to obsolete success profiles long after they stop predicting performance. AI does not guarantee fairness, but it can move decisions closer to evidence and further from intuition.
4. AI can make bias visible rather than invisible
One of the most underestimated benefits of AI is its diagnostic power. Algorithms can reveal patterns humans prefer not to see. Disparities in performance ratings, promotion velocity, pay progression, or feedback language are often dismissed as anecdotal until AI surfaces them at scale.
When bias remains implicit, its easy to deny. When its quantified, it becomes discussable. Used transparently, AI can help organizations audit their own behavior and hold themselves accountable.
For example, AI can help identify whether specific interview questions (or interviewers) are driving unexpectedly uneven outcomesso that the questions used are more likely to help pick the most qualified candidates. Importantly, this shifts bias reduction from moral aspiration to operational reality.
5. AI can slow us down at the right moments
Bias thrives under speed, pressure, and ambiguity. Many of the most consequential workplace decisions are made quickly, under cognitive load, and with incomplete information.
AI can introduce friction where it matters. By flagging inconsistent judgments, prompting justification, or suggesting structured criteria, AI can act as a cognitive speed bump. It doesnt remove responsibility from humans. It reminds them that intuition isnt always insight.
6. AI can help us understand ourselves, not just others
Bias does not only distort how we judge other people. It also shapes how we see ourselves. Research on self-assessment consistently shows that people are poor judges of their own abilities, impact, and behavior. We overestimate our strengths, underestimate our blind spots, and rationalize patterns that others notice immediately.
AI can help close this self-awareness gap.
One increasingly common use case is AI as a coach or reflective mirror. Unlike human feedback, which is often delayed, filtered, or softened, AI can analyze large volumes of behavioral data and surface patterns that individuals struggle to see on their own. This might include identifying communication habits that derail meetings, emotional triggers that precede conflict, or leadership behaviors that correlate with disengagement in teams.
Consider how AI is already being used to summarize feedback from performance reviews, engagement surveys, or 360 assessments. Rather than relying on selective memory or defensiveness, individuals can see recurring themes across contexts and time. This reduces self-serving bias, the tendency to attribute successes to skill and failures to circumstance.
The same logic explains the growing popularity of AI as a therapeutic or coaching aid. AI systems dont replace trained professionals, but they can prompt reflection, ask structured questions, and challenge inconsistencies in peoples narratives. Because AI has no ego, no reputation to manage, and no emotional investment in the users self-image, it can sometimes feel safer to explore uncomfortable insights with a machine than with another human.
Of course, self-awareness without judgment is not the same as wisdom. AI can highlight patterns, but humans must interpret and act on them. Used responsibly, however, AI can help individuals recognize how their intentions differ from their impact, how their habits shape outcomes, and how their own biases show up in everyday decisionsand it can help monitor and reinforce progress to support lasting change
In that sense, AIs most underappreciated debiasing potential may not lie in correcting how we evaluate others but in helping us see ourselves more clearly.
A necessary note of caution
None of this implies that AI automatically reduces bias. Poorly designed systems can amplify inequality faster than any individual manager ever could. Debiasing requires intentional choices: representative data, continuous monitoring, transparency, and human oversight.
The real danger is not trusting AI too muchits using AI carelessly while pretending its neutral.
Bias is a human problem before its a technological one. AI simply forces us to confront it more explicitly. Used well, AI can help organizations move closer to the meritocratic ideals they already claim to valueand that help organizations be successful. Used badly, it will expose the gap between rhetoric and reality.
The question is not whether AI will shape workplace decisions. It already does. The real question is whether we will use it to reinforce our blind spots, or to finally see them more clearly.
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Roblox, a gaming app used by nearly half of the entire U.S. population of under-16s, has rolled out a new mandatory safety feature to put a stop to children communicating with adults on the platform.
Starting on January 7, players in the U.S. were required to submit to facial age estimation via the app to access the chat feature, although age verification remains optional to play the games themselves.
Users in the U.K., Australia, New Zealand, and the Netherlands are already required to complete an age check to chat with other users, but the requirement will now roll out to the U.S. and beyond.
The verification is being processed by a third-party vendor, Persona. Once the age check is processed, Roblox says it will delete any images or videos of users.
If the age-check process incorrectly estimates a users age, the decision can be appealed and the child’s age verified through alternative methods. Users 13 or older may also opt for ID-based checks.
Once users complete the age check, they are assigned to one of six age groups (under 9, 9-12, 13-15, 16-17, 18-20, and 21+). Users can only communicate with players directly above and below their own age group. For example, a 9-year-old cannot chat with users older than 15, and a 16-year-old can only chat with those ages 13 to 20.
The feature is designed to prevent children younger than 16 from communicating with adults. About 42% of Roblox users are younger than 13.
“As the first large online gaming platform to require facial age checks for users of all ages to access chat, this implementation is our next step toward what we believe will be the gold standard for communication safety,” wrote Matt Kaufman, Roblox’s chief safety officer, and Rajiv Bhatia, its head of user and discovery product, in a blog post.
Parental consent is still required for users younger than 9 to access chat features, while age-checked users 13 and older can chat with people they know beyond their immediate age group via the Trusted Connections feature.
Leveraging multiple signals, [Roblox is] constantly evaluating user behavior to determine if someone is significantly older or younger than expected, the company execs continued. In these situations, we will begin asking users to repeat the age-check process.
The face scan is launching as the company faces increased scrutiny over child safety on the app. Attorneys general around the country are investigating Roblox, and nearly 80 active lawsuits accuse Roblox of enabling child exploitation, with some parents alleging their children encountered predators on the app.
Just four days into the new year, awards season kicked off with the Critics Choice Awards. One week later, it’s time for the Golden Globes to shine.
The 83rd edition of this star-studded eventwhich takes place on Sunday, January 11, in Beverly Hills, Californiacelebrates greatness in both television and film. Heres everything you need to know about the big night, including how to tune in.
History and past controversy of the Golden Globe Awards
The Hollywood Foreign Press Association (HFPA), the former organization behind the Golden Globes, was founded in 1943. Under this banner, journalists came together to create an awards ceremony to honor the artists they covered. The first event took place the following year, in 1944.
A 2021 Los Angeles Times article revealed several issues within the HFPA, including a complete lack of Black members. This caused many organizations and individuals to boycott the 2022 Globes. NBC declined to air the ceremony, Tom Cruise gave awards back, and several studios distanced themselves.
Because of HFPAs many issues, the organization was dissolved and the Globes were sold to Penske Media Eldridge, becoming a for-profit institution.
Many are critical of this venture, viewing it as a conflict of interest, as the L.A. Times reported. Penske also owns Dick Clark Productions, the producer of the Globes, and several trade publications such as Variety, Rolling Stone, and The Hollywood Reporter.
Who is hosting the 83rd Golden Globes?
Despite the ongoing debate, the show must go on. Funny lady Nikki Glaser will emcee the event for her second year in a row.
She will be backed up by many talented presenters, such as George Clooney, Julia Roberts, Macaulay Culkin, Kevin Hart, Snoop Dogg, Priyanka Chopra Jonas, Queen Latifah, and Regina Hall.
Heated Rivalry fans will delight in seeing stars Hudson Williams and Connor Storrie outside of the “boy aquarium.”
Where are the 83rd Golden Globes being held?
The 2026 Golden Globes Awards will take place at the Beverly Hilton Hotel. This has been its permanent venue since 1961.
Who is being honored at the 83rd Golden Globes?
This is the first year that the Globes are presenting Golden Week, featuring multiple events leading up to the big night.
One of these is a new prime-time special called Golden Eve, during which the Cecil B. DeMille Award and the Carol Burnett Award, for outstanding contributions in film and television, will be formally presented.
Helen Mirren will receive the former, and Sarah Jessica Parker, the latter. This event aired on Thursday, January 8, but if you missed it, you can watch it after the fact on Paramount+.
Who is nominated for a 2026 Golden Globe Award?
In the movie world, One Battle After Another, Paul Thomas Andersons dark action comedy, leads the pack with nine nominations.
Closely on its heels is the Norwegian film Sentimental Value, starring Stellan Skarsgrd. Ryan Cooglers Sinners has seven nods, while Chloé Zhaos Hamnet received six.
Both Wicked: For Good and Frankenstein were honored with five nominations.
In the television realm, HBOs White Lotus continues its dominance at the Globes with six nominations, while all of Netflixs shows combined received 22.
The proposed merger between Netflix and HBO’s parent company could potentially increase Netflixs laurels. Adolescence came in second place with five nods. Only Murders in the Building and Severance tied for third with four each.
How to watch the Golden Globes pre-show
If you are in it for the fashion, you have red-carpet-arrivals viewing options. The official Golden Globes pre-show will be hosted by Varietys Marc Malkin and Angelique Jackson. It begins at 6:30 p.m. ET and can be viewed for free on Fire TV, Varietys YouTube channel, or Variety.com.
Live From E!: Golden Globes 2026 will be hosted by Zuri Hall, Justin Sylvester, and Keltie Knight from 6 p.m. to 8 p.m. ET. It is available on the E! network and Peacock.
How to watch the 83rd Golden Globes
Now onto the main event: The 83rd Golden Globes ceremony will air on the CBS broadcast network and on the Paramount+ streaming service.
The awards take place tonight (Sunday, January 11) from 8 p.m. to 11 p.m. ET.
You will need the Paramount+ Premium service to stream the event in real time. Those with Paramount+ Essential subscriptions will have to wait until the next day to view the awards show.
If Paramount+ is not in your streaming arsenal, consider other live-TV streaming services that carry CBS, such as DirecTV, Fubo, or Hulu + Live TV.
Just be sure to double-check regional differences before committing to another monthly subscription.
And remember that CBS is free if you have an over-the-air antenna.
When the inevitable robot uprising comes, Ill be ready, thanks to some valuable lessons I picked up at CES. First, if given the choice of a dance off versus hand to hand combat, opt for the fight. Second, wear a cup when you do.
Robotics company Unitree showcased its G-1 humanoid robot at the show. The G-1 is a rarity in the robotic world in that its already on the market for under $15,000. Unitrees booth was an ongoing spectacle, surrounded by people eager for a close look at the dapperlooking unit, wearing a white shirt and button down vest, showcasing impressive dance skills, throwing down moves that even Shabba-Doo and Bugaloo Shrimp could respect.
There was another G-1, too — this one with a decidedly more combative directive.
By sheer luck, I found myself being asked if I’d like to strap on the gloves and go a round with the G-1. After being force-fed the technology for the better part of a week, I wasnt going to turn down an opportunity to whale on a robot.
The fight seemed fixed from the start, though. The G-1 had headgear. None was offered to myself or any other meatbag who stepped into the ring. Its gloves were a cherry red pair from Everlast. The ones velcro’d onto my hands? Salmon colored.
As the fight started, I knew I had a few advantages and a few disadvantages. The robot had me beat on strength and stamina, but I had the reach on it. I also had just enough boxing knowledge to know that the best approach was a combination of jabs and upper cuts and to keep my distance.
What I didn’t count on was that my height advantage meant that when the robot began swinging, it was mostly at crotch level.
I landed several solid shots on its chest cavity, sometimes hard enough to push it back and make it stagger — but, good grief, can that thing take a hit. It just kept coming.
The G-1 was terrible at protecting its head, so I focused my next round of punches square in where its nose would have been, had it had to worry about things like oxygen (which, by that point, I was gulping). That hardly slowed it down, but it might have caused some traumatic cranial injuries, as the robot then threw a wild punch combination in the air, completely off target.
In the interest of science, I did allow it to land a few hits (with my hip turned). While it wasnt utilizing all of its robotic strength when it hit me, I could feel it.
After about four minutes, the robot laid down on the ground and pretended to be knocked out — the company’s way of saying “Ok, time for someone else to have a turn.” When it hopped back up, we posed for a picture together. But I swear it looked ready to throw a few more jabs my way.
There are few things more evocative of the free American spirit and the nations wide-open spaces than the image of a Harley-Davidson motorcycle zooming down a stretch of empty highway. But while taking one of the legendary hogs for a spin may still be liberating for riders, the companys independent dealership owners are feeling an increasingly tight financial and business squeeze.
A rash of reports in recent weeks have sounded alarms about the troubles Harley dealers face, and the rising number of dealerships closing shop as a result. While Harley-Davidson still counts more than 650 of those locations in operation across the U.S., specialist automotive media warn that those numbers have been significantly decreasing as sales of the beefy motorcycles decline, and dealer operating costs grow.
I hate to admit this, but there are too many dealers for the number of new vehicles that are being sold today, second-generation Harley dealership owner George Gatto told the motorcycle publication RevZilla. Margins on the new bikes are the worst weve ever seen . . . Theyre not making any money.
As a result, owners of a growing number of Harley-Davidson dealerships have hung the Closed sign for good. Those include some well-known, high-profile stores in New York City and Florida, and the century-old Dudley Perkins location in San Francisco. But reports say many more closures in smaller cities and towns across the U.S. drew far less attention while adding to the tally of shuttered businesses.
That turn of events marks a swift reversal of Harley-Davidsons fortunes, and now leaves many independent dealers and the mother company itself fighting for survival.
As was the case with many companies selling comparatively expensive goods, the effects of COVID-19 created a sales boom for Harley-Davidson and its dealers. Government stimulus checks and rock-bottom interest rates allowed some consumers whod never had the money to afford a hog to buy one after 2020. More conservative consumers whod had the funds but waited also took the plunge.
Meanwhile, as happened in the auto sector, disrupted supply chains limited Harley inventories, allowing dealers to charge top dollar to customers they added to increasingly long waiting lists. Business had never been so good.
Flush with rising revenue, many dealership owners splurged on upgrades and expansions of their showrooms. Those who didnt were eventually obliged to do so by Harley-Davidson corporate policies that require dealers to abide by centralized rules, and adopt decisions made by the mothership.
But once those dealership improvement investments were madedriving occupation, heat, and maintenance costs higher as a resultthe sales boom petered out. Consumers facing spiking inflation, rising interest rates, tightening job markets, and other hardening realities of post-pandemic life could no longer give $24,000 to $40,000 Harleys another thought.
But at the same time, motorcycles churned out by manufacturers seeking to catch up with demand continued flowing into showrooms, further boosting dealer inventory costs. The same was true of Harley-Davidson-branded motorcycle equipment.
Even as that gear gushed into dealerships, Harley-Davidson corporate managers continued developing their booming e-commerce platform, which cut out intermediaries like dealers by selling directly to consumers.
They overproduced, so what do they do? Gatto said of the converging developments that cost dealers dearly. They mark it down 40%, 50%, 60% online, with free shipping. Why would you go into a dealership when youre getting half off online?
According to the recent reports, Harley-Davidsons corporate leadershipnow led by new CEO Artie Starrs, who took over in Octoberresponded to the downturn by shrinking the list of centralized rules dealers must follow. The company reduced other requirements, including minimum inventory volumes, to help ease financial pressure on dealership owners.
While that may ease some of the pain, the fear is that continually falling demand may prove the far more dangerous threat. The COVID-era boom aside, Harley-Davidsons unit sales have dropped by 45% over the past decade. That was again reflected in the companys third quarter 2025 results, which reported a global sales decline of 6%5% in the U.S.
Those latter figures led Morningstar analyst Jaime Katz to warn that it will take a lot of work, and a lasting return of robust sales, for Harley-Davidson and its independent dealers to start riding easy again.
There is little evidence that a recovery for motorcycle demand is in the cards anytime soon, Katz wrote in an investors memo following third-quarter results. After multiple years of inventory reduction at dealers, the firm has yet to find equilibrium and has signaled further unit reductions to protect dealer profitability.
By Bruce Crumley
This article originally appeared on Fast Companys sister site, Inc.com.
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