Creative agencies are struggling to integrate AI into their workflows, despite the technology’s transformative potential for the industry. Jules Love, founder of Spark AI, a consultancy that has worked with over 60 creative firms, argues that the primary barrier to AI adoption isn’t technical capability—it’s psychological resistance and poor implementation strategies.
Love emphasizes that AI adoption requires deliberate action and accountability. “Adopting AI in your team won’t happen by accident,” he told Business Insider. “You need to do it deliberately—make somebody accountable for it, and give them the space to be successful in that role.”
His six-point framework for AI integration includes:
1. Building dedicated AI taskforces: Rather than vague innovation committees, agencies need specific individuals responsible for AI integration, even if it means reducing billable client hours temporarily. Successful agencies treat AI as a core business priority.
2. Implementing role-specific training: Love criticizes the common practice of rolling out tools like ChatGPT or Gemini without proper training. He compares untrained teams to people facing “a giant box of Lego with thousands of bricks inside, but no picture on the front and no instructions.”
3. Creating structured experimentation time: Companies like Lego and Canva exemplify this approach—Canva even paused normal operations for an entire week to explore AI applications across departments.
4. Fostering psychological safety: When employees hide their ChatGPT use from colleagues, it signals a toxic culture around AI. Leaders must normalize AI experimentation and create spaces for sharing both successes and failures.
5. Treating AI as a collaborative partner: Teams should “brief” AI systems like colleagues, providing context and constraints rather than using them as glorified search engines.
6. Measuring outcomes over speed: Love warns against the “race to the bottom” that occurs when agencies only focus on doing work faster. He advocates for outcome-based pricing models rather than billable hours, allowing firms to invest in learning without eroding margins.
Looking toward 2027, Love predicts agencies that fail to embrace AI will appear “pretty old-fashioned, pretty expensive, and pretty uninteresting.”
Key Quotes
Adopting AI in your team won’t happen by accident. You need to do it deliberately—make somebody accountable for it, and give them the space to be successful in that role.
Jules Love, founder of Spark AI consultancy, emphasizes that AI integration requires intentional leadership and dedicated resources rather than hoping teams will organically adopt new tools on their own.
It’s amazing how many agencies roll out ChatGPT or Gemini to their teams and don’t train anybody on it.
Love criticizes the common practice of providing AI tools without proper training, comparing it to giving someone a massive Lego set without instructions or a picture of what to build.
Fear kills innovation faster than bad tools. You have to give a little bit of room for failure.
Love highlights the importance of psychological safety in AI adoption, noting that constant deadline pressure prevents teams from experimenting with new workflows and discovering innovative applications.
If all we’re doing is doing more stuff faster, then we’re going to see a bit of a race to the bottom on fees.
Love warns that agencies focused solely on speed will commoditize themselves, urging leaders to shift from billable-hour models to outcome-based pricing that rewards quality and innovation rather than velocity.
Our Take
Love’s framework addresses a fundamental truth about technological transformation: tools alone don’t create change—culture does. His emphasis on psychological safety and structured experimentation aligns with research showing that fear of job displacement often creates the very resistance that prevents workers from developing AI skills that would protect their careers.
The shift from billable hours to outcome-based pricing represents a profound business model disruption that extends beyond creative agencies. As AI accelerates knowledge work across sectors, professionals who cling to time-based value propositions will find themselves competing on price rather than expertise. Love’s advice to “stop thinking about what you can do today more quickly and what you can do tomorrow better” encapsulates the strategic mindset required for the AI era—focusing on enhanced capabilities and novel solutions rather than mere efficiency gains. Agencies that successfully navigate this transition will likely emerge as industry leaders, while those that resist may face obsolescence by 2027.
Why This Matters
This story highlights a critical inflection point for the creative industry as AI tools become increasingly sophisticated. While technology companies race to develop more powerful AI models, the real bottleneck to transformation lies in organizational culture and change management—not technical capability.
Love’s insights reveal that the creative sector faces an existential challenge: agencies must fundamentally rethink their business models, moving from time-based billing to outcome-based pricing, or risk commoditization. This shift has broader implications for knowledge workers across industries who face similar pressures to demonstrate value beyond speed and efficiency.
The emphasis on psychological safety and structured experimentation time also reflects emerging best practices in AI adoption. Companies that create space for failure and normalize AI use are more likely to discover innovative applications that provide competitive advantages. For business leaders, this article serves as a roadmap for cultural transformation in the AI era, emphasizing that successful integration requires dedicated resources, accountability, and a willingness to challenge traditional workflows and pricing models.
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Source: https://www.businessinsider.com/how-creative-agencies-can-future-proof-their-teams-for-ai-2025-10