Side by side with AI : Trampoline’s Guide to Safe Innovation

What if 60% of your team's tasks could be automated – without sacrificing quality, losing control, or compromising security?¹

Every era has its technological revolution, and this one is powered by AI.

At Trampoline, we don’t see AI as something to fear, but rather as the next step in evolving our ways of working. It’s reshaping roles, setting new standards for security and data protection, and is encouraging our teams to build new skills while staying in control of their work.Discover how our strategists, designers, and developers are using AI in their day-to-day work: from practical prompts and favourite tools, to pitfalls to avoid, and most importantly, how to ensure every use of AI is responsible and secure.

AI as a Talent Multiplier

Strategy

Our analysts and AI tools form a strong, complementary duo. AI quickly surfaces patterns and emerging signals, and our strategists leverage that information to investigate root causes and craft thoughtful, actionable recommendations that stay aligned with business priorities. Our analysts leverage their critical thinking abilities to ensure coherence across projects. With AI features like “Deep Search,” our analysts can explore niche topics in seconds, broaden their thinking, and sharpen their action plans. AI also helps give structure and language to emerging ideas, helping strategists bring clarity to their vision.

Rihem - strategist at Trampoline says: “AI gets the puzzle started – but it takes our know-how to put it all together.”

Favourite prompt: “Start by breaking this complex concept down like you’re explaining it to your ten-year-old student. Then, take it a step further by highlighting what’s most relevant to my specific context.”

Favourite tool: ChatGPT

Design

Our design teams turn to AI as a creative catalyst, using it to push their thinking further and explore unexpected directions in their UX process. From app structures and visual design suggestions to conceptual starting points, AI helps spark ideas and streamline early-stage exploration. In copywriting, for instance, it lays down a solid base that guides the development of visuals and mockups across multiple concepts.

An AI assistant helps our design team to save time. That said, when it comes to delivering standout creative work, there’s no substitute for the trained eye and artistic sensitivity of a human creator. That’s why our designers move fluidly between AI and human input, drawing on the strengths of each, depending on the needs and constraints of the project. The time saved allows our teams to focus on what really matters: innovation and creativity. They can quickly filter through the most promising concepts, experiment with visual tone and direction, fine-tune interfaces, and add the human touch that sets great design apart. Their energy is channelled into crafting bold, original ideas and refining every visual detail, so each project faithfully reflects the client’s brand DNA.

Joanna - designer at Trampoline says: “AI is our go-to creative assistant across disciplines – UX, UI, copywriting, art direction… we use it wherever it adds value.”

Favourite prompt: “Write the most effective prompt to generate a photorealistic image based on this moodboard. Include lighting, mood, depth of field, texture, and camera angle.”

Favourite tools: ChatGPT & Sora

Development

Our developers use AI to enhance coding and debugging, while maintaining full control over architecture and structure. AI also automates repetitive tasks: generating blocks of code, test data generation, and format conversions. It’s also a great tool for embedding context directly into the code, through comments, docstrings, and annotations, which fuels richer documentation and supports long-term maintainability. Each output is reviewed, and examples are refined to cover edge cases. The result is a synergy between AI and developer that speeds up the process while ensuring robust, scalable solutions.

Stanley - developer at Trampoline says: “AI is here to stay. It speeds up 60% of my repetitive coding, but I’m still essential when it comes to architecture and security. That’s where my expertise really shines.”

Favourite prompt: “Analyze this function, describe its goal, provide a detailed explanation of how it works, and identify its external dependencies.”

Favourite tool: Claude AI

Operations & Daily Workflow

Beyond specific use cases, AI is woven into the rhythm of our workday, streamlining tasks across the board. It helps reorganize schedules by suggesting priorities, speeds up email and content writing with adaptive templates, and simplifies both summarization and note-taking. When it comes to research, it instantly surfaces key takeaways and relevant references from long texts.

At Trampoline, we continuously explore new tools to make the most of these productivity gains. Here are some of our go-tos:

• Notion AI – for generating summaries and smart to-do lists
• Perplexity – for ultra-targeted web research and factual answers
• RunwayML – for prototyping videos and visual effects without complex workflows
• Granola – for meeting notes and recap writing
• Wispr Flow – for voice-assisted drafting (prompts, messages, emails, etc.)

Keep in mind that these AI tools are still evolving and gradually implementing best practices for data handling, so it’s important to carefully manage the access and permissions you grant them.
Paired with our internal safeguards, these tools help us save hours each week, allowing us to focus on what really matters: innovation, quality, and time with our clients.

But even with all its benefits, AI has its limits, which is why we treat it as a tool that enhances, not replaces, human judgment.

Contextual Limitations

AI is trained on historical data, which means it can fall short when faced with new or unfamiliar use cases. It often lacks the situational awareness and common sense needed to adapt to novel contexts.

Bias and Discrimination

Without strong oversight, AI can reproduce the biases and blind spots embedded in its training data, undermining fairness and equity in processes.

Factual Hallucinations

At times, AI can “hallucinate”, fabricating references, statistics, or facts that have no basis in reality. This can lead to flawed assumptions and misinformed strategic decisions.

Black Box and Traceability

Many AI systems function as black boxes: they process your data, run complex calculations, and deliver answers, without revealing how they got there. This lack of transparency is a real concern. If a recommendation or diagnosis is challenged, it can be nearly impossible to explain the logic behind it or trace its origins. To maintain trust and meet regulatory requirements, it’s essential to have at least a basic view into the reasoning, such as step-by-step “reasoning chains” or simplified activity logs.

Data Protection

Finally, every prompt or data point sent to an AI model can potentially expose sensitive information if not properly filtered or isolated in a secure environment. That’s why our confidentiality protocols are essential at every stage.

How AI Can Reinforce Your Data Security

Adapting to AI also means thinking seriously about security. At Trampoline, AI isn’t just a productivity booster—it’s also a key ally in protecting data.

We’ve built AI into our in-house products as a gatekeeper, reinforcing safety and control by design. With the support of cybersecurity partners, we train our teams to use AI tools that monitor data flows in real time, spot anomalies or leaks, and isolate risks before they cause harm. And we don’t wait for problems to appear. Before any prompt is submitted, we systematically clean and anonymize sensitive data to reduce risk exposure. It’s important to remember that many AI tools store and reuse inputs, which is why these types of precautions matter.

Data readiness is a cornerstone of our approach: data cleaning, classification, and pseudonymization are built into our model training workflows. Everything is done in accordance with relevant regulations, like Europe’s GDPR or Quebec’s Law 25, to ensure privacy compliance at every step.

While AI keeps evolving, threats like prompt injections and jailbreaks remain real. That’s why we follow security research closely, like Anthropic’s recent bug bounty initiative² to test their defences against sensitive info leaks. These efforts help us continuously improve our own AI safety posture.

Golden Rules for Safe AI Adoption in Your Organization

1. Map Your Use Cases and Flag Sensitive Areas

• List all tasks where AI could boost efficiency (emails, forecasting, visual prototyping, etc.)
• For each use case, identify:
  • The type and sensitivity of data involved
  • The potential impact of errors (reputation, cost, compliance
• Rank them by risk to guide oversight and select the right AI tools

2. Sign a Data Processing Addendum (DPA)

• Choose enterprise-level plans with your AI vendors and sign a DPA to lock in their commitments to data protection
• Business-tier plans typically include:
• Dedicated data storage
• Minimal retention policies
• Advanced access controls
• But not all vendors offer this, so verify their terms carefully
  

3. Set Up Human Oversight and Share Best Practices

• Add manual validation for critical tasks:
  • Editorial review before publishing AI-generated content
  • Unit testing and approval before deploying AI-generated code
• Create shared protocols:
  • Internal prompt templates
  • Clear rules for allowed data formats
• Combine human oversight with shared standards to ensure safe, scalable adoption

Example of poor AI usage:

Klarna – $99M loss due to “over-automation”³
The fintech’s CEO publicly emphasized the replacement of 700+ customer service reps with AI chatbots. By Q1 2025, the result was a steep drop in customer satisfaction and a surge in disputes and refunds, leading to $99 million in net losses. It’s a stark reminder: AI can scale impact, but it still needs a human touch to steer it right.

Want to Dig Deeper?

Looking to grow your AI maturity and upskill your teams? Here are some resources we recommend:

• Book: The Second Machine Age by Brynjolfsson & McAfee – how tech revolutions unleash human creativity
• TED Talk: “How to Make AI That’s Good for People” by Sheila Ng (TED2023) – human-AI co-creation
• Podcast: Lex Fridman #452 – Dario Amodei (CEO of Anthropic) on Claude, AGI, and AI’s future
• Article: “Power to the People” by Andrej Karpathy – how LLMs are democratizing tech
• Newsletter: Import AI by Jack Clark – weekly digest on AI breakthroughs, ethics, and ecosystem shifts

So, Now What?

With the right tools and the right people, AI can be your ally in unlocking new levels of performance. You could boost productivity⁴ freeing up your teams to create even more value.

¹McKinsey & Company, The state of AI: Insights from our QuantumBlack practice, April 2025

²Anthropic Research, “Tracing thoughts in a language model: An explainability approach” (2025)

³Futurism, “Klarna CEO bragged about replacing workers with AI – then reported millions in losses,” February 2025

⁴McKinsey & Company, The state of AI: Insights from our QuantumBlack practice, April 2025