Wearemaybetech

02/10/2026

Most companies are already getting value from AI, but too many are treating that progress like a secret.

In our groundbreaking whitepaper, The Big AI Secret, we unpack a pattern we keep seeing in the data: 7 in 10 organisations report measurable ROI from AI adoption, yet only 38% talk about those wins externally. That silence is not neutral. It quietly hands competitors a positioning advantage, and it leaves customers and candidates guessing whether you are keeping up.

The gap is driven less by reality and more by fear. 61% of leaders worry about brand perception if they discuss AI openly, even as 84% of customers expect companies to use AI to deliver better service. When expectation is high and communication is low, trust does not increase, it erodes.

What we heard in 1,500+ interviews was consistent: teams fear an authenticity backlash, they worry competitors will copy them, they downplay “small” use cases, and they get stuck in legal uncertainty. But your buyers rarely care whether you built a custom model. They care that you can deliver faster insights, more relevant work, and better outcomes, reliably and responsibly.

High performers don't talk about AI as a buzzword. They talk about measurable benefits, specific use cases, and how AI augments their people rather than replacing them. They also prepare for the question that is increasingly standard in pitches and procurement: how are you using AI to serve us better?

If you're seeing AI ROI internally, consider what silence is costing you externally: missed deals, weaker differentiation, slower talent attraction, and fewer opportunities to lead the market conversation.

Read the blog: Why Companies Stay Quiet About AI Success (And How It Hurts Growth) and take a clear, practical approach to communicating AI progress with confidence.

🔗 https://www.maybetech.com/blog/why-companies-stay-quiet-about-ai-success-and-how-it-hurts-growth

Maybe* research shows 70% of firms see AI ROI, but only 38% share it. Discover how transparency about AI wins builds trust, talent, and competitive advantage.

02/10/2026

"AI has become everyone's job, but no one's responsibility. It's all happening in silos without coordination or measurement. If you don't join it up, AI can't do the thing it's meant to do, which is get work done faster." - Polly Barnfield, Maybe* founder and CEO.

Many businesses are embracing AI, but few are taking true ownership.

It's essential to have a clear AI strategy that aligns with your brand values and business goals.

By connecting AI solutions, businesses can enhance efficiency, drive innovation, and ensure consistent decision-making.

01/10/2026

Most AI discussions get stuck on model quality: who writes best, who reasons best, who searches best.

That matters, but it’s not the bottleneck for many teams.

The bottleneck is that “great output” often doesn’t translate into “completed work.” If a tool produces a draft or a summary and then stops, the remaining steps, sending, updating systems, assigning owners, scheduling next actions, still rely on people and process.

That’s why “answering vs acting” is a useful lens. Chatbots and research tools are strong at generating content and insights. They are weaker out-of-the-box at connecting to your day-to-day systems and completing multi-step workflows reliably. An ex*****on layer is designed specifically to close that gap: take an instruction or a trigger and produce a finished, auditable outcome inside the tools your business already runs on.

If you’re evaluating AI, don’t judge it by a demo prompt alone. Run a small operational test. Pick one workflow with clear inputs and outputs lead follow-up, meeting actions, weekly risk review . Define what “done” means in your business systems. Then see whether the tool completes the steps consistently without manual glue work.

Start with one task. Head to our blog for a full breakdown of AI tool examples and comparisons 👉 https://www.maybetech.com/blog/why-ai-tools-leave-work-undone-ex*****on-layer

Most AI tools answer, but work still stalls. Learn the “ex*****on layer” that turns prompts into completed tasks inside Slack, Teams, CRM, and your workflow.

01/10/2026

The first and most important thing Maybe* and Liganova MaSH! built together was not an AI Agent. It was an interface.

Spud lives inside Microsoft Teams. It’s the architecture behind every single chat the team uses to access help across resourcing, files, compliance, insight, and audience testing. It’s not “just a bot”. It’s an orchestration layer that connects the systems you already rely on, while keeping the day-to-day experience simple.

It’s easy to assume powerful AI has to look complicated. In practice, complicated surfaces are where adoption goes to die. We built Spud to feel small and familiar, because that’s what makes teams actually use it. Spud lives inside Teams, so people don’t have to learn a new interface or change how they work. They message one agent in the same place they already plan projects and share updates. The simplicity’s deliberate, not accidental.

Behind that single Teams chat is the iceberg. Spud orchestrates several capabilities that remove daily admin without replacing human judgement. Brand compliance checking happens as work’s created, so reviews focus on decisions rather than repetitive checking. Resource planning connects to Float, so availability can be confirmed and booked quickly when a brief shifts. File finding connects to Box, so teams can search in plain language instead of digging through folders. News can be delivered by topic, client, or brief, so insight arrives without extra tabs. Synthetic audiences can help teams test and refine ideas earlier, which can change what an agency can offer, not just how fast it delivers.

If you’re exploring AI for your organisation, start with one question. Will your team have to go somewhere new to use it, or will it meet them where they already work? Read the blog to see why we believe the surface is the strategy.

🔗 https://www.maybetech.com/blog/iceberg-principle-spud-simple-by-design-part-2

30/09/2026

Bridging the Gap: AI Meets Human Insight in Business

In an evolving digital landscape, the conversation has shifted from whether to use AI to how best to integrate it with human expertise. At Maybe*, we're exploring how businesses can strike this crucial balance.

The Dynamic Duo
AI excels at crunching numbers, identifying patterns, and automating repetitive tasks. Meanwhile, human judgement brings invaluable skills like emotional intelligence, ethical reasoning, and contextual understanding. The real magic happens when these strengths come together to create something greater than the sum of their parts. ✨

Crafting the Ideal Collaboration

Define Clear Roles:
-- Let AI handle data-heavy, repetitive tasks.
-- Reserve complex decision-making for humans.
-- Create workflows that leverage both capabilities.
Empower Your Team:
-- Train your staff to confidently use AI tools.
-- Foster a culture of continuous learning.
-- Encourage critical thinking and creativity.
Maintain Human Oversight:
-- Implement regular audits of AI systems.
-- Ensure transparency in AI processes.
-- Keep humans in charge of strategic decisions.

Success in Action:
Imagine healthcare professionals using AI for initial diagnostics but making the final decisions themselves. Picture financial advisors leveraging AI for market analysis while maintaining personal client relationships. Envision creative teams using AI for content suggestions while preserving their brand voice and emotional connection.

The Golden Rules
Start small and scale gradually.
Prioritise ethical considerations.
Regularly review and adjust strategies.
Focus on enhancing, not replacing, human capabilities.

The key? Allow AI to take care of the mundane so your team can focus on what humans do best: innovate, create, and connect.

Ready to find your perfect AI-human balance? Let Maybe* show you how to transform your business operations while keeping human expertise at the heart of your success. Get started today.

🔗 http://www.maybetech.com/blog/how-can-businesses-strike-a-balance-between-relying-on-ai-and-maintaining-human-judgement

Learn how businesses can effectively integrate AI with human judgement to enhance decision-making. Discover Maybe* strategies for defining roles, promoting collaboration, and maintaining ethical oversight for a successful AI-human partnership in diverse industries.

30/09/2026

"Anybody who says, 'We can't do it because the token cost is too great', it's the ROI conversation. If you're not getting ROI, it means you haven't defined the output you want, and you're not asking the right question. If you're worried about the token cost, the question to ask is, 'With the output I'm getting, what would it cost to deliver that normally?' And therefore the token cost is a fraction of that output." - Polly Barnfield, Maybe* founder and CEO, at the Mida Roundtable, May 2026.

Token costs matter, but focusing on the pennies per prompt can distract developers from the metric that actually ships value, which is ROI.

When you measure cost alongside time saved, defects avoided, conversion lifted, and support load reduced, you can justify the right model, the right context window, and the right guardrails for production.

Do optimise tokens, but optimise outcomes first, and your AI spend becomes a predictable investment rather than a creeping line item.

29/09/2026

Maybe* is changing the AI game via our integration with Make. You can connect to over 2,000 essential business tools, creating a seamless and powerful automation experience.

Imagine automating your workflows without writing a single line of code. With this integration, you can connect your favourite tools like Slack, Salesforce, and HubSpot, eliminating manual data entry and reducing operational friction. It's all about working smarter, not harder.

This isn't just about convenience, it's about transformation. Picture your marketing team automatically generating and scheduling social media content, or your customer service team building automated support workflows that connect multiple touchpoints. The possibilities are endless.

But the real magic happens with our multi-LLM approach, combining the capabilities of OpenAI, Anthropic's Claude, Perplexity, DeepSeek, Gemini, Mistral, Grok and Stable Diffusion. This powerhouse of AI models allows you to generate and distribute content, analyse data, and create sophisticated problem-solving workflows, all while maintaining enterprise-grade security. 🔒

The integration is live and ready to revolutionise your business processes. Whether you're looking to enhance operational efficiency or provide 24/7 customer support, AI Agents from Maybe* and Make have you covered.

Curious about how this integration can benefit your organisation? With Maybe*, it can be your reality. Get started today and learn more about how to harness the power of AI Agents in your business strategy.

https://www.maybetech.com/blog/maybe-announces-game-changing-integration-with-make-connect-your-ai-to-2000-business-tools

Discover Maybe*'s latest integration with Make, enabling seamless AI connectivity with over 2,000 business tools. Automate workflows, enhance productivity, and drive innovation with enterprise-ready security. Learn how this game-changing update can transform your business operations today.

29/09/2026

If retention work is taking over your calendar, you’re not doing it wrong. You’re doing it properly, and that is the problem.

A high-performing retention methodology demands constant attention to signals, tight timing windows, and a lot of manual reconciliation across the stack.

groa° founder Emma Powell built Retention-First Growth® and proved it through outcomes:

Brands consistently hit Klaviyo top-decile performance.
Repeat purchase rates landed at 40 to 50 percent, where 15 to 20 percent is typical.
Dormancy stayed below 30 percent.
The results were repeatable, but the workload was heavy, around 70 hours per month to sustain one brand at that level.

groa° is designed to remove that 70-hour tax without cutting the corners that make retention-first work effective. It does that by embedding the methodology into AI Agents that run continuously.

Maybe* is the AI ex*****on layer behind that decision.

We’ve been building the infrastructure that lets multiple agents coordinate, keep identity and signals unified across Shopify, Klaviyo, and third-party tooling, and execute interventions where the team already works.

That’s how the methodology becomes an operating system, rather than a playbook that depends on someone having time to run it.

You keep control and judgement.
The work that should complete itself finally does.

Read more in our blog: https://www.maybetech.com/blog/groa-maybe-retention-first-agents-operating-system-part-1

28/09/2026

AI’s hardest problem was never the model. It was the organisation.

We’re proud to share that Maybe* Founder and CEO, Polly Barnfield, is among the nominees for Computer Weekly’s Top 50 Most Influential Women in UK Tech.

This year’s list also shows something fascinating when you focus on the job titles. AI roles are rising fast, and many are about adoption, enablement, governance, assurance and ethics, not about building models.

That shift tells you where the real work is now: embedding AI into everyday workflows, keeping a human accountable for outcomes, and making sure results are safe and trustworthy.

We’ve written a blog on what these titles reveal, plus a simple way to start: pick one defined piece of work, change how it gets done with AI, measure the impact, then repeat.

Read the blog and share it with someone who is responsible for turning AI into outcomes, not experiments.

🔗 https://www.maybetech.com/blog/the-job-titles-that-prove-ais-hard-part-was-never-the-technology

UK organisations are creating AI adoption, enablement and governance roles fast—far more than “builder” roles. Here’s what those job titles reveal about where AI really succeeds: ex*****on, accountability and trust.

28/09/2026

When businesses talk about what they want from AI, the first word we hear most is “faster”. Faster reporting. Faster content. Faster customer replies. Faster everything.

Speed is appealing because it is easy to imagine, and easy to justify. But speed can also be the quickest way to spend money on AI and change very little.

Here’s why: If you make a task faster, you still keep the task. Someone still owns it, starts it, checks it, and finishes it, every week. The workload stays the same shape, just slightly compressed, and the saved minutes disappear into the noise of a busy calendar. That’s why “faster” can be expensive, not only in budget, but in attention. It can use up an organisation’s appetite for change on the most comfortable version of AI.

The more valuable question is different. Not “how do we do this quicker”, but “does a human need to do this at all”? That question is harder, because it asks you to redesign the flow of work and be honest about what your people should spend their time on. But it’s also where AI starts to create structural impact.

In our blog, we explore the shift from optimising tasks to removing them, where “faster” is a feature, but “gone” is a strategy.

Read the full piece via the link below, and let us know: what's one recurring task you would like to remove from your week for good?

🔗 https://www.maybetech.com/blog/faster-is-the-most-expensive-word-in-ai