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How User Interviews Can Be Accelerated with an AI-Powered Insights Platform

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Harriet, the first full-stack AI solution designed to get companies’ internal data ready for the AI revolution, relieve People teams of their daily admin burden, and give every staff member their own HR assistant, has raised a £1.2m pre-seed round led by Concept Ventures and joined by Frontline Ventures, Portfolio Ventures, and Notion Capital. 

What’s actually eating your research timeline – and why the fix isn’t what most people expect.

Nobody skips user research because they don’t care about users.

They skip it because the last time they tried, two weeks of recruiting ended with three cancellations. The sprint didn’t wait. Someone made a judgment call, the feature shipped, and everyone quietly agreed they’d do it properly next time — which is what they said the time before that too.

Next time never really comes.

AI-powered research platforms are worth paying attention to right now, not because they make research feel futuristic, but because they remove the specific friction that makes teams abandon it in the first place. That’s a more boring claim than most vendor marketing would make – and probably a more useful one.

The Interview Itself Is Rarely the Problem

A 45-minute conversation with a user isn’t what kills research timelines. What kills them is everything around it.

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Recruitment for a niche persona – say, a head of operations at a logistics company with 50 to 200 employees – can take three weeks on its own. Then you’re coordinating schedules across time zones. Then someone’s dog has a vet appointment and they reschedule, which cascades into your analysis window. Transcription, tagging, theming. Pulling together a synthesis doc that stakeholders will actually read. By the time that’s done, the decision you were trying to inform has already been made – or worse, you’ve held it up.

This is what researchers mean when they talk about the infrastructure tax. The research itself is a relatively small part of the timeline. The coordination surrounding it is enormous.

AI platforms specifically target that tax. Not the conversation, but everything before and after it. That’s a narrow claim but an important one, because it changes what you should expect these tools to do and what you shouldn’t.

What These Platforms Actually Do

The category is still early enough that a lot of what gets labeled “AI research” is just survey tools with a chatbot bolted on. Worth distinguishing that from platforms genuinely rearchitecting the workflow.

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The more interesting approach involves synthetic personas – AI-generated user profiles built from demographic, psychographic, and behavioral parameters relevant to your target market. Rather than finding and scheduling real participants, you define who you want to hear from, and the platform constructs representative personas accordingly. Then it run automated interview sessions with those personas: the AI moderates, adapts follow-up questions based on what the persona “says,” and runs multiple sessions in parallel. What would normally take three weeks of logistics happens in under an hour.

The synthesis piece is where a lot of the time savings actually land. Traditional research often ends with a pile of transcripts that still need a human to code, theme, and interpret. These platforms produce structured analysis – hypothesis validation, theme identification with supporting evidence, pattern recognition across personas – as part of the output. You’re not starting from raw data.

One thing worth noting: synthetic personas sidestep a few real problems with live interviews. Politeness bias (participants saying what they think you want to hear) goes away. So does incentive distortion – the way a $75 gift card quietly changes how someone responds. Whether those tradeoffs net out positively depends on what you’re trying to learn, which brings up the more nuanced question.

Where This Works and Where It Doesn’t

Synthetic research is genuinely well-suited to a specific category of work: concept validation, messaging tests, pricing sensitivity, feature prioritization, early hypothesis pressure-testing. Situations where you want directional signal before committing resources, not ethnographic depth.

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What it’s not designed for: longitudinal behavior tracking, use cases where existing behavioral data is sparse or nonexistent, or research where the texture of lived experience is the actual insight you need. A team building tools for people managing chronic illness, for example, should be talking to real people. The emotional specificity of that context matters in ways a synthetic persona can’t replicate.

Most teams who get this right don’t treat it as either/or. Synthetic research handles the high-frequency, lower-stakes validation work – testing messaging before a campaign goes live, checking whether a new nav pattern makes sense before engineering builds it, running a quick concept test before a sprint kickoff. Live interviews get reserved for the contextual, strategic work that actually needs them.

That division of labor is less philosophically interesting than the debate about whether AI can replace human insight (it can’t, fully), but it’s far more practically useful.

What Changes When Research Gets Cheaper and Faster

Here’s the part that doesn’t get talked about enough: when research is slow and expensive, it gets rationed. You do it on the big decisions – new product lines, major redesigns, significant pivots. Everything else ships on instinct.

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That’s not negligence. It’s math. A two-week study doesn’t make sense for a microcopy change or a nav restructure or a pricing page tweak. So those decisions get made without data, and sometimes they’re fine, and sometimes they compound into a product that technically works but keeps missing the mark with users in ways nobody can quite diagnose.

Lower the cost and time of research to 30 minutes, and the calculus changes. A PM tests three different onboarding flows before the engineering ticket gets written. A founder checks whether a landing page angle actually resonates with their target segment before spending on ads. A designer validates a navigation pattern while the Figma file is still open. None of these are decisions that would have justified a traditional study. All of them produce better outputs.

Agencies feel this particularly acutely. Research has traditionally been a premium offering – something you include on the big retainers, not the smaller project work. Faster, cheaper tools change what you can viably include in a scope. That has real downstream effects on what you can charge for, what you can defend in a pitch, and what your clients walk away trusting.

The cumulative effect of running more validation – across smaller decisions, earlier, when there’s still room to change direction – is hard to quantify neatly. But teams that do it consistently tend to make fewer expensive late-stage corrections.

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Starting Out: What the First Run Actually Looks Like

If you haven’t used one of these platforms before, the first session is usually less complicated than expected. You describe what you want to learn – the idea, the problem you’re testing, the assumption you’re trying to pressure-test. You define your target user in reasonably plain terms. The platform handles persona generation, interview design, execution, and synthesis.

Articos structures this as five steps: define the idea, generate personas, shape the interview questions, run the sessions, review the analysis. First time through, most people are done in 30 to 40 minutes. The output is a structured report – not raw transcripts – with themes, hypothesis validation, and supporting quotes from the sessions.

A practical starting point: pick something your team is already debating. A feature that’s been stuck in prioritization discussions. A pricing structure you’ve never properly tested. A headline you’re running on gut. Run a study on it before the next planning meeting and bring the output. That’s usually enough to shift how the team thinks about doing this regularly.

The teams that get the most value from these platforms aren’t treating it as a one-off. They block time – weekly, sometimes more often – to run a study the way they’d block time for a retrospective or a design review. Not because it’s a habit that feels productive, but because it keeps decisions connected to actual user behavior rather than drifting toward internal opinion.

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Where This Is Headed

User research has been slow and expensive for a long time, and that’s shaped how teams think about it – as something you invest in seriously or skip entirely. The middle ground, where you validate things quickly and often on decisions of all sizes, hasn’t really existed at scale before.

That’s what’s starting to change. Not the underlying value of talking to users – that hasn’t changed – but the economics of doing it frequently enough to matter.

For teams that figure out how to fold this into their normal working rhythm, the compounding effect is real. More validation, earlier, on more decisions. Fewer expensive surprises six months into a build. More confidence in the things you ship.

It’s worth paying attention to, even if you’re skeptical. Especially if you’re skeptical – because the case for faster research isn’t that AI has solved the hard problem of understanding users. It’s that the logistics were always the part holding most teams back, and those are now genuinely solvable.

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Wall Street Traders Are Pouncing on the Tariff Refund Chaos

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Wall Street Traders Are Pouncing on the Tariff Refund Chaos

Wall Street smells an opportunity in the chaos over President Trump’s tariffs.

The Supreme Court’s tossing of Trump’s sweeping tariffs last week

kicked off a scramble among business leaders to sort out what might come next—including how they might claw back the levies they have been paying to import goods from around the world.

Copyright ©2026 Dow Jones & Company, Inc. All Rights Reserved. 87990cbe856818d5eddac44c7b1cdeb8

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How to Keep Your Email Marketing Up to Date in 2026

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How to Keep Your Email Marketing Up to Date in 2026

Digital marketing has changed a lot over the years. The days of non-targeted ads, desktop-first web design and mass communication blasts are all but behind us. With that in mind, many wonder whether it’s worth doing email marketing at all in 2026. While digital marketing and email techniques have evolved, there’s no need to think of emails as obsolete in this age’s cyber landscape. 

Modern emails need to be AI-optimised, personalised and technically sound, among other things. This article will offer guidance on proper digital agency techniques to benefit your email marketing metrics, keeping the marketing channel alive well into the back half of the 2020s. 

Personalisation is everything in email marketing

For those wondering how to create an effective email marketing campaign, personalisation is king. Personalisation has become more important in every facet of marketing and promotion. It’s no longer enough to use someone’s first name as a way of showing you “care”. Batch-and-blast email marketing will easily get you blacklisted as spam. 

  • Real-time behavioural actions should trigger flows and campaigns, rather than you simply sending out as many generalised newsletters as possible. Say a customer repeatedly views a page about a specific product. That should trigger an email with information about the product.
  • Software like HubSpot can swap out email sections based on past behaviours and purchases, ensuring people aren’t greeted by irrelevant listings. 

Generalisation kills engagement. Use data to drive your email offerings. 

Optimise your emails for AI 

People with email marketing jobs have already embraced generative AI in terms of creating outlines or even building emails from scratch. However, these days, much like your average Google search, many email providers will create AI summaries, meaning people might not even read the whole thing. 

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  • Provide a proper value proposition in plain HTML text, not in a graphic.
  • Use H1 and H2 tags to display a clear hierarchy throughout the content of the email.
  • Place the most important information in the first 50 words for the AI to understand.

Artificial intelligence is here to stay, so you need to know how to work with it, rather than trying to bypass it in email marketing. 

Make data collection more consensual

Privacy laws are tighter than ever, and for good reason. However, this does mean traditional data tracking can be a little more complicated, which is why you need to make the collection of the data more of a cooperative thing. 

  • Allow subscribers the chance to set their preferences during sign-up, ensuring you never overload them with quantity or unwanted information. 
  • Use interactive polls and questionnaires inside your emails to capture data willingly, which is also likely to increase the details offered.

This is a more compliant and effective way to collect data than ever before, which will allow for personalisation to be even more optimised. 

Technical must-haves for a good email marketing career in 2026

Starting with a weak technical foundation is cancerous to your email marketing campaigns. You won’t even reach the Promotions tab, being destined to exist solely in the realm of spam communications. 

  • DMARC, SPF and DKIM are all essential authentication steps to eliminate the possibility that you’re a ‘spoofer’.
  • Accessible layouts, colour schemes, easy-use buttons and Alt-Texts are all essential for maximising user friendliness.
  • Optimising your imagery and text for ‘Dark Mode’, which is very popular. 

A solid technical base is key for the rest of your efforts to be effective.

These guidelines aren’t just pieces of advice for your campaigns; they’re absolute essentials for anyone trying to capture the success of a dedicated email marketing agency. Email marketing can very easily become outdated without the right approach, but when you put modern techniques first, it can remain a valuable part of any 2026 plan,

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Crypto Fund Trader Review: Is It the Most Transparent Prop Firm in 2026?

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Crypto Fund Trader Review: Is It the Most Transparent Prop Firm in 2026?

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Greener Routes, Smarter Logistics: The Evolution of Sustainable Last Mile Delivery

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Greener Routes, Smarter Logistics: The Evolution of Sustainable Last Mile Delivery

Sustainability is no longer a side initiative in logistics. It is a defining factor in how companies design, manage, and optimize their last-mile delivery operations. As e-commerce continues to expand, the final leg of the delivery journey has become both the most visible and the most environmentally impactful stage of the supply chain.

For multifamily properties, student housing communities, and corporate campuses, this shift has created a new operational reality. Digital tools such as automated mailroom software are now central to supporting sustainable last-mile delivery strategies while maintaining efficiency and service standards.

Why the Last Mile Matters Most

The last mile is often the shortest segment of the delivery journey, but it accounts for a disproportionate share of emissions and costs. Multiple delivery attempts, inefficient routing, traffic congestion, and fragmented drop-off points increase fuel consumption and carbon output.

At the property level, unmanaged parcel flows add to the problem. Delivery drivers may spend excessive time locating package rooms, waiting for access, or making repeat visits when residents are unavailable.

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“Sustainability in last-mile logistics begins where the truck stops.”

Improving this final handoff point is one of the most practical ways to reduce environmental impact without compromising convenience.

The Rise of Centralized Parcel Management

As delivery volumes surge, properties are moving away from informal package handling processes. Instead, they are adopting structured parcel management systems that consolidate deliveries and reduce friction.

By leveraging centralized parcel management software platforms designed for high-volume environments, properties can support more efficient parcel management workflows while minimizing unnecessary driver dwell time.

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When delivery personnel can complete drop-offs quickly and accurately, routes become more efficient. Fewer delays at each stop translate into lower fuel consumption across entire delivery networks.

A comparison of traditional and sustainable approaches illustrates the shift.

Operational Element Traditional Last Mile Model Sustainable Optimized Model
Delivery Attempts Multiple attempts per package Consolidated, first-time acceptance
Package Intake Manual and time-consuming Barcode scanned and logged instantly
Driver Wait Time Extended due to access issues Streamlined access and drop-off process
Resident Notification Delayed or manual Automated real-time alerts
Environmental Impact Higher emissions per stop Reduced idle time and route inefficiencies

The difference lies not only in vehicles or fuel types, but also in operational coordination at the delivery destination.

Digital Mailrooms as Sustainability Enablers

Modern properties are increasingly implementing intelligent mailroom systems to manage growing parcel volumes. Through automated logging, resident notifications, and secure tracking, these systems eliminate many inefficiencies that historically plagued last-mile delivery.

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Communities adopting integrated mailroom software solutions for sustainable mailroom management are finding that digital infrastructure directly contributes to environmental goals.

Here is how:

  • Reduced repeat delivery attempts through secure package acceptance
  • Faster drop-offs that lower vehicle idle time
  • Organized storage that prevents lost or misplaced parcels
  • Data insights that support better staffing and scheduling

When drivers can complete deliveries in minutes rather than navigate confusion, emissions decline incrementally across thousands of stops.

“Sustainability is built on small operational improvements repeated at scale.”

Consolidation and Smart Locker Integration

Another key development in sustainable last-mile delivery is consolidation. Instead of individual doorstep drop-offs, many properties are encouraging centralized package rooms or locker systems.

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Consolidated delivery points create measurable environmental advantages:

  • Fewer stops within a property
  • Reduced internal vehicle circulation
  • Improved route density
  • Lower overall fuel consumption

Digital parcel management platforms help coordinate these consolidated deliveries by ensuring every item is logged, tracked, and communicated to residents without delay.

In student housing and multifamily communities, this approach also enhances security and resident satisfaction while aligning with broader sustainability initiatives.

Data Driven Environmental Accountability

Sustainable last-mile strategies increasingly rely on measurable performance indicators. Property managers and logistics partners alike are turning to analytics to assess environmental impact.

Mailroom management systems provide valuable operational data, including:

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  • Volume trends by day and season
  • Average pickup turnaround time
  • Peak delivery windows
  • Carrier performance metrics

When this data is shared with logistics providers, both parties can refine delivery schedules and reduce congestion during high-volume periods.

For example, staggering carrier arrival times or allocating dedicated delivery windows can reduce vehicle clustering and minimize idling-related emissions.

Data also supports corporate sustainability reporting. As organizations track Scope 3 supply chain emissions, efficient parcel intake processes contribute to measurable improvements.

Supporting Alternative Delivery Models

Sustainability in the last mile is not limited to electric vehicles or bike couriers. It also involves operational readiness to support evolving delivery models such as micro fulfillment centers, consolidated carrier partnerships, and scheduled bulk drop offs.

Properties equipped with scalable parcel management infrastructure are better positioned to adapt to these models. Without structured systems in place, carrier-level innovation can be undermined by inefficiencies at the destination.

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By integrating mailroom management software into broader property operations, managers create a stable foundation for greener logistics partnerships.

The Human Factor in Sustainable Logistics

Technology alone does not guarantee sustainability. Staff training, process consistency, and resident education all play important roles.

Clear pickup policies, timely notifications, and accessible package rooms reduce dwell time and unnecessary storage. Encouraging residents to retrieve packages promptly also improves turnover and storage efficiency.

When operational discipline aligns with digital tools, sustainability outcomes improve significantly.

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“Environmental progress in logistics is achieved through coordination, not complexity.”

Looking Ahead

As urban density increases and e-commerce continues its upward trajectory, sustainable last-mile delivery will remain a strategic priority. Carriers are investing in cleaner fleets and smarter routing algorithms, but meaningful progress also depends on the infrastructure at delivery endpoints.

Multifamily communities, student housing providers, and commercial properties play a critical role in this ecosystem. By modernizing parcel intake processes and adopting digital mailroom systems, they actively contribute to reduced emissions and more efficient delivery networks.

The evolution of sustainable last-mile delivery is not defined by a single breakthrough. It is shaped by coordinated improvements across vehicles, routes, and property operations.

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In this new landscape, the mailroom is no longer a passive recipient of packages. It is an active participant in building a more efficient and environmentally responsible logistics future.

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Why you should consider fixing your energy tariff now

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Why you should consider fixing your energy tariff now

Martin Lewis explains what the upcoming change to the energy price cap means for your bills.

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The Math Behind Trump’s Eye-Catching Economic Ideas

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The Math Behind Trump’s Eye-Catching Economic Ideas

In a record-length State of the Union address, President Trump threw out a string of eye-catching economic ideas. Among them: new retirement accounts for Americans without access to 401(k)s; replacing income taxes with tariff revenue; balancing the federal budget by eliminating fraud; and lowering the cost of housing for buyers while preserving high home values for happy homeowners.

His proposals and promises come as American voters are increasingly frustrated with the economy. About 56% of Americans disapprove of his handling of it, compared with about 40% who approve, according to an average of polls collected by the nonpartisan Cook Political Report.

Copyright ©2026 Dow Jones & Company, Inc. All Rights Reserved. 87990cbe856818d5eddac44c7b1cdeb8

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Why I'm Still Bullish On Novo Nordisk Despite Recent Setbacks

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Why I'm Still Bullish On Novo Nordisk Despite Recent Setbacks

Why I'm Still Bullish On Novo Nordisk Despite Recent Setbacks

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Baron International Growth Fund Q4 2025: Contributors, Detractors, And Trades

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Baron International Growth Fund Q4 2025: Contributors, Detractors, And Trades

Baron is an asset management firm focused on delivering growth equity investment solutions. Founded in 1982, Baron has become known for its long-term, fundamental, active approach to growth investing. Baron was founded as an equity research firm, and research has remained at the core of its business. Note: This account is not managed or monitored by Baron Capital, and any messages sent via Seeking Alpha will not receive a response. For inquiries or communication, please use Baron Capital’s official channels.

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Girls’ Generation’s Tiffany Young, Byun Yo Han Are Now Married

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Tiffany Young and Byun Yo Han
Tiffany Young and Byun Yo Han
Tiffany Young / Instagram

K-Pop star and Girls’ Generation member Tiffany Young and actor Byun Yo Han are officially married.

The couple has registered their marriage, which means that they are legally considered married despite not holding any wedding ceremony.

Tiffany Young and Byun Yo Han Are Married

According to The Korea Times, Byun’s agency TEAMHOPE confirmed the marriage in a statement to the couple’s fans.

“Actors Tiffany Young and Byun Yo Han completed their marriage registration today, based on deep trust in and love for one another,” TEAMHOPE said in the statement.

“We also feel cautious and concerned that the continuing news might cause some fatigue,” the company continued. “However, the two actors told us they wanted to share the news first with their fans, who have always watched over them with great love, and we are informing you of this out of respect for their wishes.”

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The couple met when they co-starred in the Disney+ drama “Uncle Samsik.” They confirmed their relationship last December.

Will They Hold a Wedding Ceremony?

While no wedding ceremony has held upon the registration of their marriage, the couple is planning to hold a small ceremony, according to Korea JoongAng Daily.

This, again, was confirmed by TEAMHOPE.

“They are carefully considering holding a small wedding with family members in order to pay their gratitude, in the form of a [church] service,” the company said.

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UK car production falls 13.6% in January as exports weaken, SMMT reports

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Britain’s car manufacturing output has slumped to its lowest point in more than seven decades after a devastating cyber attack brought Jaguar Land Rover’s (JLR) assembly lines to a standstill for more than a month.

Society of Motor Manufacturers and Traders (SMMT) has reported a sharp contraction in UK vehicle output at the start of the year, with total production down 13.6 per cent in January as weaker export demand weighed heavily on the sector.

A combined 67,415 vehicles left British factories during the month, comprising 65,249 cars and 2,166 commercial vehicles. Car production declined by 8.2 per cent compared with January 2025, while commercial vehicle output slumped by 68.6 per cent year on year.

The fall was primarily driven by reduced overseas demand. Although domestic appetite for UK-built cars remained broadly stable, export volumes softened, particularly in markets outside Europe. Exports typically account for the majority of British vehicle production, leaving manufacturers exposed to fluctuations in global demand and trade conditions.

The United States remained the second-largest destination for UK-built cars after the European Union, accounting for 14.1 per cent of exports. Japan followed with a 2.7 per cent share, while China and Turkey took 2.5 per cent and 2.4 per cent respectively.

Electrified vehicle output also declined. Production of battery electric vehicles (BEVs), plug-in hybrids and hybrid models fell by 10.6 per cent to 26,854 units, representing 41.2 per cent of total car output. Despite the drop, electrified vehicles continue to form a substantial share of UK production as manufacturers transition towards zero-emission platforms.

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The industry body said the weak start to the year reflected subdued global demand and underlined the importance of stable trade relationships. Protectionist measures and “made in Europe” proposals in some markets were cited as additional headwinds.

Mike Hawes, chief executive of the SMMT, described January’s figures as disappointing but pointed to expected recovery later in the year as new electric models enter production.

“Weak exports to markets beyond Europe amid soft demand delivered a disappointing start to the year for UK vehicle manufacturing,” he said. “It reinforces the need for a forward-looking trade agenda that secures existing preferential access and builds new ones with markets worldwide.”

The SMMT expects overall car production to increase by more than 10 per cent to around 790,000 units in 2026, with the potential to reach one million vehicles by 2027, provided new model launches proceed on schedule and investment conditions remain supportive.

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The outlook hinges on competitive energy costs, a strong domestic market and targeted supply chain support, the trade body said, as the sector continues its capital-intensive shift towards electrification.


Jamie Young

Jamie Young

Jamie is Senior Reporter at Business Matters, bringing over a decade of experience in UK SME business reporting.
Jamie holds a degree in Business Administration and regularly participates in industry conferences and workshops.

When not reporting on the latest business developments, Jamie is passionate about mentoring up-and-coming journalists and entrepreneurs to inspire the next generation of business leaders.

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