Morning, everybody. This is half one, the first half of 2026 for S4 Capital.

I'm actually in New York. Wes is in Las Vegas at an AI conference.

Scott is in London with Radhika, our CFO. We've got five areas to go through.

First are the results themselves, which Radhika will just take you through. Secondly, market momentum from Scott.

Wes will talk a little bit about artificial intelligence and with a demonstration of what we've been doing. Then I'll finally give a brief summary and outlook, and we'll go to Q&A.

With that as background, over to you, Radhika.

Thank you, Martin. Good morning, everybody.

I will start with the financial headlines for the first half of 2026. Despite global macroeconomic pressures, technology clients and hyperscalers continuing to further prioritize AI investment, and ongoing client caution, disciplined cost management has delivered a very strong first-half operational EBITDA with a significantly improved EBITDA margin.

Liquidity focus has also lowered our net debt. Net revenue was £308 million, down 6.2% reported and 4.7% like-for-like.

Operational EBITDA was £38 million, compared to £20.8 million in the first half of 2025, with a margin of 12.3%, up 600 basis points reported and 710 basis points like-for-like. Adjusted operating profit was £35.2 million, and adjusted basic earnings per share was 2.7 pence versus 0.2 pence in the first half of 2025.

The board has approved an inaugural interim dividend of 1.35 pence per share, 50% of the adjusted basic earnings per share. The company generated £10.4 million in free cash flow, and net debt reduced to £66.3 million, which is 0.7 times pro forma 12-month operational EBITDA, significantly below the £145.9 million on the 30th of June 2025.

The company has now met the reduction of its term loan B target, repurchasing a further €40.1 million, subject to settlement. This reduces the outstanding term loan B to €249.7 million.

Moving on to the P&L. Revenue for the period came in at £344 million, which is down 4.6% on a reported basis and 3.2% like-for-like.

Net revenue for the period was £308 million, down 6.2% reported and 4.7% like-for-like. This reflects what has been a volatile macroeconomic environment, exacerbated by the Middle East conflict, in conjunction with technology clients and hyperscalers further prioritizing AI investment.

In response to these conditions, we have continued our disciplined approach to cost management, and the first-half EBITDA performance reflects the annualized impact of the cost actions taken in the second half of 2025, which primarily focused on non-billable roles and back-office efficiencies. Personnel and operating expenses were reduced by 12.6% on a reported basis.

The company's aim is to align personnel cost to net revenue ratios more closely to industry averages. As at the half year, this was 72.2% compared to 79.2% for the first half of 2025.

At the end of the first half, the total number of Monks fell to approximately 6,150, which was down 11% compared to this time last year and down 3% compared to December 2025. Looking across our two practices, Marketing Services and Technology Services, my commentary now is all on a like-for-like basis.

Marketing Services delivered net revenue of £281.9 million, a 4.4% decline, reflecting ongoing caution among technology clients as they continue to further prioritize and increase AI infrastructure over operational marketing budgets. The practice was further impacted by a scope reduction in BMW, which impacted the EMEA region.

Technology Services generated £26.1 million in net revenue, down 7.4%, similarly impacted by broader macroeconomic headwinds and extended sales cycles. From a regional standpoint, the Americas, which represent 80% of our total net revenue, declined 0.8%; EMEA declined 20.3% and represented 14%; and Asia Pacific declined 12.5%, representing 5% of our mix.

Turning to operational EBITDA by practice, on a like-for-like basis, Marketing Services delivered £44.1 million, an increase of 72.3% compared to the first half of 2025. EBITDA margin strengthened to 15.6%, up 690 basis points, reflecting decisive headcount actions and continued cost discipline.

Technology Services generated £4.4 million, up 214.3% from the first half last year. EBITDA margin strengthened to 16.9% and improved by over 1,000 basis points, underlining the effectiveness of our cost control measures.

Moving on to the debt and balance sheet slide. We maintain a strong balance sheet throughout the period, with strong liquidity and long- and long-dated maturities.

Our M&A obligations are now largely complete. Stronger treasury management and a focus on liquidity reduced period-end net debt to £66.3 million.

Leverage closed at 0.7 times net debt over pro forma 12-month operational EBITDA, below our target of 1 times and below our key covenant of 4.5 times. The company met the targeted reduction of its term loan B, repurchasing a further €40.1 million, subject to settlement, reducing the outstanding term loan B to €249.7 million.

Moving to the cash flow. Free cash flow was £10.4 million in the period, compared to £16 million in the first half of 2025.

The movement was driven by an expected Q1 2026 working capital outflow. This was primarily due to a combination of stronger year-on-year Q4 2025 collections and lower year-on-year Q4 2025 media billings.

As collections normalized and trading strengthened, working capital improved in the second quarter. Capital expenditure in the period was £2.7 million, up just under 30% from the first half of 2025 of £2.1 million, due to ongoing investments in AI capabilities.

Financing costs reduced meaningfully, driven by the reduction in our net debt and the average effective interest rate improving to approximately 5.7%, down from 6.1%. Improved cash management increased interest income to £1.9 million, and tax paid in the period was higher, at £3.8 million, driven by utilizations of tax losses in 2025.

Restructuring and transformation costs in the period were £5.7 million, primarily £3.9 million due to restructuring costs and £1.4 million related to our finance transformation program. Moving on to the net debt bridge.

Net debt at 31st of December was £86.9 million or £79.6 million at closing June 2026 exchange rates. The company generated £10.4 million of free cash flow during the period.

The company repurchased €85.2 million of its term loan B at a discount of €4.9 million. These movements resulted in a lower closing net debt position of £66.3 million, again representing 0.7 pro forma 12-month operational EBITDA, below the targeted leverage of 1 times.

Our capital allocation priorities are maintained from the year end. We have established a clear capital allocation priorities, focusing on delivering shareholder value through first, dividends; second, targeted debt repurchases; and third, share buybacks.

The board has implemented a 50% dividend payout policy out of adjusted basic earnings per share over the medium term, subject to financial targets being met. We now move on to guidance.

2026 full-year like-for-like net revenue is now expected to be down mid-single digits. Operational EBITDA remains at the current analyst consensus level of £85 million, with operational EBITDA margin targeted to increase by 140 basis points.

Year-end net debt range has been lowered to £50 to £80 million. In line with our targeted operational EBITDA, we aim to maintain leverage of under 1 times.

The company has repurchased a further €40.1 million, subject to settlement, of the term loan B. This reduces the outstanding term loan B to €249.7 million.

Our forecast net finance expense has been lowered to £19 to £21 million, excluding the one-off gain on the loan repurchase. The effective tax rate is expected to be 28% to 30%.

Adjusted basic earnings per share will now be in excess of current analyst consensus. With that, I will hand over to Scott for the market update.

Thank you very much, Radhika. Good morning, and thank you, everyone, for joining the meeting today.

I'm going to cover some of the dynamics we're seeing in our wider market, and then share some specifics on our client relationships, before handing over to Wes for an update and a demo on our artificial intelligence product. As you can see, digital marketing spend continues to increase at significant rates, whilst overall advertising spend is growing at around 5%, meaning analog spend continues to decline.

The revenues at the top platforms continue to grow in the high teens, significantly outpacing the market growth. One thing to bear in mind here is that 80%-plus of their revenues come from small and medium-sized businesses, and they continue to expand their market share there.

Their growth is not necessarily being driven by enterprise client spend. The technology services market continues to have lower growth compared to recent historical double-digit performance.

2025 had just over 5% growth, and whilst enterprises continue to invest in areas such as cloud and AI, the outlook for '26 continues to be subdued. The next slide charts the comparison between agency and revenue growth at the main public holding companies, and advertising spend and GDP growth.

Digital spend now represents around 70% of the total, and as I mentioned on the previous slide, is growing at high single-digit rates, meaning analog is in decline. Agency growth dipped to almost 0% in 2025, and has decoupled from advertising spend and GDP growth.

One explanation for this is the continued pressure from clients to maintain their media spend, but to put pressure on what they call non-working spend, i.e., agency spend. This is particularly the case with technology clients.

The next slide looks at the relationship between capex spend and sales and marketing spend at the major tech companies: Amazon, Meta, and Alphabet. As historically almost half our revenues come from this sector.

Prior to 2022, marketing spend at the top platforms regularly grew at 20% annual rates, and has now essentially been flat since then. On the other hand, capex spend, particularly on AI and infrastructure, has ballooned in the same period, growing over 140%.

This trend is expected to continue, with the hyperscalers already announcing plans to increase their capex spend almost 90% in 2026, and some of them committing to similar increases in 2027 already. The tech companies are unsurprisingly leading the charge on adopting AI in their marketing workflows, and leveraging it to achieve more for the same or less.

We continue to have a very compelling client list with some of the world's leading and most innovative companies. Eight of them are what we call whoppers, and that's revenues of $20 million-plus, which continues to be a differentiator for a company of our scale.

As you can see, we continue to be skewed towards the tech industry, with around 42% of our revenues coming from technology. These are strong relationships that help us attract and retain talent to work on them.

Spends per client are slightly down, but essentially stabilizing versus the previous year across our top 10, 20, and 50 client cohorts, and the focus now is very much on returning all of them to growth. With that, I'll hand you over to Wes for an update on our artificial intelligence approach.

Thanks.

Thank you, Scott. Hi, everyone.

AI update. The last update we did was very much focused on the work, and I'll start with a little bit of work today as well.

We had this up and running in Cannes about a month and a half ago for Google, one of our clients, at Google Beach. A very fun use of their Gemini Omni video model, which honestly is pretty amazing for this type of personalization.

This is not my actual outfit in Vegas; this is all AI-related. What I'm going to do today is talk a little bit about our discussions in Cannes.

Cannes is one of the two big moments we have every year to put a little bit of a stake in the ground, the other one being CES. If we go to the next slide, our focus really was how does the technology help clients win the race to relevance?

I think we showed last time, when we showed a bunch of work, that efficiency is table stakes. Efficiency is mostly down to vision and decision-making.

I think what is more interesting is how does the technology help clients generate more demand, capture that demand, grow their business, grow their brand. To do that well, we have to move away from thinking about an ad and more moving towards what we call system thinking.

The system thinking part is something that we've been proving out with clients over the last six to nine months. If we go to the next slide, we started building it into our go-to-market earlier in the year.

Not sure if people on the call know AdForum as an organization, global organization that brings pitch consultants together to visit agencies in a specific region. They'll visit 30 to 35 agencies, score those agencies on the relevance, relevance to the market, relevance to their clients, relevance to the RFPs that they see in their pipeline.

We did that in May. Monks ended up being scored the number one most relevant agency.

This was I think quite an interesting takeaway quote, meaningfully ahead of our competitive set. We're of course seeing that play out in some of our pipeline already.

These are very connected folks that have quite a meaningful impact on pipeline in general. It's also sometimes a little uncomfortable to be ahead.

We do believe in the current landscape it's important to be close to the edge of what's happening, because that edge is moving more and more quickly. I think our ability to stay close to that edge helps us understand how the technology evolves, how it dissipates into marketing, and what that means for marketing organizations, which are our clients.

That's a little bit of framing. If we go to the next slide, the way we think about growth is through two lenses.

One, we need to do work that is loved by humans. That's traditionally how we've thought about advertising, marketing, creative.

I think the way people currently interact and interface with content is very different to five years ago, 10 years ago. People are spending an inordinate amount of time on their phones.

I think it's about 13 hours a day, and a lot of that time is spent scrolling. More and more, to be loved by humans, we have to be part of that constrained environment.

We have to be part of these micro-cycles of attention. Then we need to do work that is preferred by machines.

Some of that is about algorithmic media, where there's a massive preference for volume, variation, variety, velocity, all of the V's. Of course, more and more, how do LLMs and agents sort of surface brands within the sort of agentic ecosystem?

That was our main focus during Cannes. What I'll do now, and I'll spend about 10 minutes on that, is show the environment that we showed our clients a month and a half ago from MonksFlow.

I think we should be switching screens now. Let me know when it's up.

Are we good to demo?

Yep, we're good. Amazing.

Thank you so much. First a little bit of positioning.

MonksFlow started as an internal project two and a half years ago. I think we saw early what most large enterprise organizations are now finding out, is that pilots don't necessarily contribute to P&L impact.

It's very difficult to capture productivity gains if everybody's piloting. We moved to very fixed processes, which allowed us to double down on best practices.

That process-heavy movement we were early when it came to jumping on agentic workflows. Last year at Cannes, MonksFlow was the first agentic marketing platform.

The positioning of MonksFlow currently I think is really quite unique. It's not vibe-coded.

It's not one-off. It's enterprise-grade, safe, secure, scalable, auditable trails when it comes to everything that happens within the platform environment across your teams, lots of high productivity per token, really making sure every token counts.

Then, we operate at a much higher clip than traditional SaaS products, who are stuck in 3, 6, 12-month cycles. We launch updates every two weeks because our team is fully agentic-enabled, and that allows us to do more specific solutions client- to-client, which I think is quite unique.

The way we think about infrastructure for MonksFlow is three levels: intelligence, creation, and orchestration. I'll run through that relatively quickly, you get a sense of what we have.

It starts with knowledge bases. This is a very easy environment to set up knowledge bases related to clients.

In this case, we've set this up for one of our clients, Mr Muscle, part of SC Johnson. It has all of the brand information, and you can upload anything that you want here: structured, unstructured data, we can connect it to live data feeds.

Agents are able to use this context to do really meaningful, relevant work. We're not just creating that level of context, we're also adding agents that are a representation of the audiences.

That means you have a series of audience agents, in this case, the efficient mum. This is a representation of third-party data.

We bring to the table lots of interesting third-party data partnerships, first-party data if it's available. It means you have the voice of the customer everywhere in your workflow, and I'll show what that looks like in a moment.

Let's say hi to the efficient mum for a moment.

I need cleaning products that work fast, feel safe around my kids, and make my routine easier.

You get the drift. Insights on this persona: where does this persona consume their media, what's a typical brand relationship, etc., etc., etc.

You can start conversations with these personas, which can be really useful. They're also part of other tools.

This is really where we get to the creation piece. We can run focus groups with these personas, for instance, how do you decide to purchase?

Oh, let me check if that's a question. Then you can select your personas, run that focus group.

What's great about MonksFlow, my question wasn't great. It wouldn't be good at getting meaningful insights back, but that gets translated to actually meaningful questions that then get run through this agentic process.

All these personas are now being interviewed. I'll show you what that looks like.

This was one done with four people. All the interviews are available, but more importantly, it creates additional datasets that we can use in our agentic workflows.

I think a huge part of what we're doing in here is making sure our agents have lots of context to be high performing. These personas, for instance, which is quite interesting, can look at an example here, which means we can optimize content in a predictive manner that really outperforms some of the traditional algorithmic methods.

Just really useful to have these agents available. That is the intelligence layer, starts leaning into some of the tools that we have for creation.

The most important one of those tools is what we call Opportunities. If you think about doing work that people love, a lot of that is down to the insight to in-channel.

Can we capture an insight that is of value, and how quickly can we translate that insight to an in-channel asset? Because of the speed of social, speed of culture, that time is compressed.

Historically that might have taken weeks, sometimes even months, doesn't really make sense anymore. A lot of our focus has been how can we do that same day.

What you're seeing here is opportunities that are being prepped by agents. We're capturing data feeds from Reddit, from X, trending topics, news within your category.

All of that data is being reviewed close to real time by agents that do the job of what used to be a social agency, right? Social listening, social strategy.

These opportunities are already being vetted by your audiences, you get a sense of who would be interested in what type of messaging. You can vet all of the sources, you even get an idea of initial suggested channels.

This is ongoing, right? These are continuous.

You can turn these into briefs if you want as part of your projects. I'll show how projects work in a moment.

Really meaningful, really useful, gives you details on things that need a really fast response, seasonal has a bit more time, of course, and then behavioral is bigger consumer change that also helps potentially drive some product development. These are really interesting.

If you want, you can start putting additional research against some of these opportunities. We call that IQ.

A great example here, for instance, is more information on what it means to be Mr Muscle in Brazil. That also adds information about your competitive set.

Agents are looking at what your competitors are doing, their media spend, their messaging. Again, lots of really useful information that also starts helping you define business opportunities.

Then of course, if we have insights and we want to get to in-channel, we need a piece of content. I'll show you how that works as well with the few minutes we have left.

Part of MonksFlow is also the end-to-end workflow. Why is that useful?

It's useful because it allows teams to work together, client and agency, but also agents to be part of that workflow. What I'll show here, for instance, is a working environment that we had running during Cannes.

Of course we had the World Cup during Cannes. As a Dutch person, not the best World Cup ever.

We spotted a really interesting opportunity, or at least the agents spotted a really interesting opportunity. The Japanese fans went viral because they were cleaning up the stadium before leaving.

Then was actually a little bit of a meme, because these were mostly men, where the meme was, 'Hey, maybe start doing some of that at home as well.' The idea was can we do a little bit of a World Cup sort of cleaning moment?

Oh, sorry, we have some sound coming through.

It's not annoying me.

What we'll show here is how we took these briefs, and these briefs are auto-generated, really best in class. You'll get agents to comment on these briefs.

Again, this sort of collaboration between people and agents is really quite unique. Then you can make content.

I'll show a piece of content here, World Cup Drama, quick explanation of what happens here. The moment you take one of these briefs, you can throw it to Studio.

Studio looks at the brief, predefines what a great reel would be. Reels are really sort of social currency, really key asset at the moment.

It auto-generates initial concepts for you. You can of course collaborate with agents to change these concepts or you can just accept them.

If you accept a concept, it then gets translated to best-in-class script for a reel, IG, TikTok, really as the main platforms. Then it generates all of the environments and images, but it does it in a way that's very on-brand, very in context.

You can also still edit, it depends a little on power users versus people that are just going through the workflow. Then you end up with an ad.

These ads are on-brand, safe to use, and really the whole workflow we just went through, from opportunity spotting to working on some of the strategy and creative and then getting to an asset, can be done anywhere between 15 minutes and an hour, which of course is a massive, massive sort of change to how these things historically happened. Lots more in here.

We were doing these demos in Cannes and took us close to 45 minutes, really powerful tool. This sort of systemic way of working also means we have more and more interesting solutions that we're launching to clients.

I'm sure we'll talk about some of those solutions in our next earnings call. With that, I'm going to hand it back to Sir Martin.

Thanks, Wes. Finally, summary and outlook.

First-half net revenue was down 6.2% reported and 4.7% like-for-like. That reflected the continuing macroeconomic uncertainty, heightened by the Middle East conflict, and combined with technology clients and hyperscalers prioritizing AI investment.

I think as we say in our release, the top four hyperscalers are spending about $5 trillion on capital investment between 20- or they're projected to, 2025 and 2030. Reported record operational EBITDA of £38 million, up almost 83% reported and 128% like-for-like, with a higher proportion of operational EBITDA in the first half compared to previous years based on the 2026 full-year target, but a stronger second half is anticipated from a bottom-line point of view.

EBITDA margin in the first half at 12.3%, up 600 basis points reported and 710 basis points like-for-like. Number of Monks down 3% to around just over 6,000 people, compared with 6,350 at December 2025 and 6,900 in June of '25 last year.

Half-year net debt at just over £66 million, which represents a leverage of 0.7 times EBITDA, down from £146 million, which was leverage of 2 times, which was reported last year at 30th of June. Full-year like-for-like net revenue expected to be down mid-single digits, and full-year EBITDA remains at current analyst consensus level of £85 million, with the margin target to increase by 140 basis points.

New business wins from LVMH, from Mercado Libre, Capital One, Revlon, Square, SEEK, Watts, and Air India. The targeted net debt range for 2026 has been lowered from £50 to £80 million- sorry, to £50 to £80 million from £60 to £90 million, and we aim for leverage to be maintained at under 1 times operational EBITDA.

The board's implemented a 50% dividend payout policy out of adjusted basic earnings per share, subject to our financial targets being met, and will recommend a final dividend for 2026 in line with that policy. The final dividend for 2025 of 1.1p was paid in July, and the board has approved a first-time inaugural interim dividend for 2026 of 1.35p per share, 50%- that represents 50% of the adjusted basic earnings per share of 2.7p.

The company has met the targeted €125 million reduction of its term loan B, and has therefore reduced the outstanding balance of that term loan B to just under €250 million. We continue to see significant opportunities for new business, particularly driven by our AI tools and capabilities as Wes has just outlined, particularly in relation to the work for SC Johnson.

Adopting from existing clients is ramping up as clients driven by existential threats in automotive, in the automotive category and vertical, in financial services, and FMCG, fast-moving consumer goods, move from pilots to fully scaled adoption, and our proprietary AI solutions at the heart of all of our new business efforts. We remain confident in our talent, in our business model, in our strategy, and our scale client relationships, which position us to deliver sustainable long-term growth.

With that, Laura, as operator, we can turn to Q&A.

Thanks all for a really good presentation there. Just a couple from me.

First, could you just expand a little bit on the predicted higher margins now and where those higher margins are going to come from? Then just on the AI side, be good to understand what you think AI will be able to do in the future that you didn't think it could do 6 months ago.

Thanks.

Right. Radhika, do you want to deal with the margin point?

Maybe Wes, you can respond on what AI enables us to do that we couldn't do a few months ago. Radhika, margins.

Our margins. The first half, as we said, was driven by really the annualized cost out impact of what we did at the back end of 2025.

We continue with our cost focus, really looking at our cost base in relation to our net revenue. For the second half as well, that's where we've got that full-year impact, and that's why we've increased it to by 140 basis points.

It's the full-year impact of what we did at the back end of last year and our continued cost management through the year.

Okay. Wes, do you want to talk a little bit about what AI enables us to do?

Yeah. We've I think always been quite clear about where we were expecting this to head, and I think that's been relatively consistent from our perspective.

I think it's probably still surprising to look at the length that agents can now work without supervision, which allows us to do much more real-time work without human supervision, because the concept of hallucinations has pretty much gone away, and agents are just very good at long-form work and holding context. The length of unsupervised agentic workflows, even though you could sort of predict it based on the line goes up, I think it's still quite surprising to see where that's already at.

Do you want to add anything to that, Wes, or? Nope.

I would just say a couple of things in relation to that. Firstly is the resistance to using synthetic material, AI-driven material, I think both from clients and from consumers, I think will decline.

The interesting thing to us about AI is that consumer adoption is moving faster than client or enterprise adoption. Now that's nothing new.

I think we saw that with smartphones, mobile phones and smartphones, and with previous technological revolutions. Whilst the industry and our clients indeed agonize over every pixel, I'm not sure that consumers do.

Increasingly, I think they will become ambivalent or neutral and maybe even positive about content which is synthetic. The other thing I would say is that we're going through, I think this is the seventh quarter of double-digit EPS growth and finished Q2 for the S&P 500.

We're going through, despite all the volatility from an earnings growth point of view, we're seeing companies perform extremely well, even excluding the hyperscalers and tech giants. EPS growth is very, very strong.

Usually, that converts into a strong advertising growth, but as Scott said, we've seen a breakdown of the correlation between agency revenue growth and GDP growth and profit growth from companies. That's we think principally driven by the tech hyperscalers' switch to capital investment versus opex.

That change takes place when there are existential threats, like autos, from Chinese EVs, AVs; financial services, when fintech platforms start to shape traditional banking structures; and with FMCGs, when pricing is more difficult to get, having increased prices during COVID or post-COVID, can't do it anymore, consumer resistance to do that, and geopolitical conflicts in Eastern Europe and in Middle East in particular disrupt supply chains. Companies are becoming more focused on efficiency.

For example, the P&G CEO yesterday on CNBC was talking about the need to move to content at scale. When you see clients under a little bit of pressure, and we may start to see that perhaps in the second half of the year as growth maybe slows globally, inflation is a little bit more persistent, and interest rates tick up a bit, if they do, we may see adoption moving quicker.

I think another thing that's going to happen is that we will see more wholesale adoption to gain the efficiency that we're talking about as maybe economic conditions tighten a bit.

Thank you. Really interesting.

All right. Thanks, everybody, for joining us.

When is it, Radhika? We're going to be a little bit earlier this year on Q3.

When will that be?

September.

Early September. We'll be back to you with Q3.

Sorry, October. I was getting ahead of myself.

Sorry, October. All right.

We will be very quick to do it in September,

but

we'll be earlier in October. All right.

Thank you very much. Thanks for joining.

Thank you. Bye-bye.

Thank you. Thanks.