This is a summary of Jukebox Podcast episode featuring Matt Schwartz, founder of Inspry, an Atlanta-based WordPress and WooCommerce agency, and creator of CheckView, a WordPress testing product. The conversation focuses less on AI generating pages and content and more on how agencies can use AI to improve internal processes, deliver more value to clients, and rethink service offerings.
Background and framing
Matt runs Inspry (founded 2011) and has been working with WordPress since 2013. He’s been engaging with many agencies about practical AI use — not the hype, but how it can be intentionally applied inside agency operations. The key idea is that AI is most powerful when applied to processes and workflows rather than simply used to assemble pixels on a page.
Why focus on process, not just product
Clients rarely see the technical differences between two websites beyond design. What they do experience is an agency’s process: how you onboard, communicate, touch base, and support them. Matt argues AI’s biggest impact will be on these client-facing workflows and internal SOPs, because execution (building a basic site) is increasingly a commodity. Agencies that lean into strategy, automation, and process improvements will differentiate themselves.
Is now the moment?
The pace of change is rapid. AI tools are making formerly expensive tasks much cheaper and faster, so client expectations are shifting. That doesn’t mean every agency must rush in; rather, those who ignore AI risk falling behind competitors who use it to improve touchpoints, responsiveness, and value. The floor is rising — clients will expect more, sooner, and often at a lower price point.
Transparency with clients
Matt’s approach: if AI materially affects the product delivered to a client, be transparent about it. For internal workflows and productivity gains that don’t change the client experience, disclosure is less necessary. Exceptions exist when the client asks for help implementing AI internally — then those processes will mirror what the agency uses and ought to be shared.
AI Vision Document: intentional adoption
One practical recommendation is building an AI vision document. This is a deliberately scoped plan that:
– Maps agency processes and identifies repetitive or time-consuming tasks.
– Flags where AI could safely add value and where human judgment must remain.
– Establishes guardrails and risk assessments so adoption isn’t haphazard.
A vision document helps keep teams aligned about what’s permissible and where human review is mandatory. It’s similar to a mission statement: writing the rules down changes how people act and gives clarity during experimentation.
AI as a service offering
For many clients, the word “AI” can be off-putting. Matt suggests packaging the outcomes of AI work as business improvements: automated workflows, internal apps, or task automation that saves money or generates revenue. Agencies can productize AI-driven services — for example, building lightweight internal apps or automation flows (using tools like n8n or Make) that were previously unaffordable for small businesses. These products can also create recurring revenue if the agency hosts or maintains them.
Data-driven marketing and insights
AI excels at aggregating and summarizing large datasets. Agencies can use it to analyze customer data, support tickets, geographic and spending trends, or conversion behavior to produce actionable recommendations. This enables agencies to offer strategic insights to clients at price points that were previously unattainable.
Practical, low-friction uses inside agency operations
Some of the most immediate, low-risk uses of AI include:
– Meeting summaries and action items: AI tools can transcribe and summarize calls, producing clear next steps and reducing the time spent drafting proposals or statements of work.
– Proposal and SOW drafting: By ingesting discovery notes, past proposals, and client materials, AI can draft customized proposals that a human then reviews and finalizes.
– Time-tracking and pattern recognition: Analyze billing or task data to find repetitive tasks that are prime for automation.
AI for support workflows
AI can improve support by aggregating context from help tickets, logs, and site data to prepare more complete issue descriptions and likely fixes for human technicians. The goal isn’t to hide customers behind a bot but to give support staff the context they need to resolve issues faster. This must be done carefully: support is a sensitive touchpoint where poor automation experiences can quickly frustrate customers, so balance and human fallback options are essential.
AI-assisted debugging and WordPress management
Connecting AI agents to WordPress sites — with strict guardrails — can speed up debugging. AI can scan logs, correlate errors across systems, and suggest fixes that would otherwise take hours to diagnose. Page builders and WordPress tooling are evolving to be more agent-friendly, enabling AI to perform edits or suggest modifications while WordPress remains the infrastructure layer.
Human oversight remains critical
Across use cases, Matt emphasizes human-in-the-loop review. AI can produce useful first drafts, diagnoses, or edits, but human checks are still required, especially where site reliability, security, or client reputation are involved. The right balance depends on risk tolerance: low-risk tasks can be more automated, while high-risk decisions demand human judgment.
Broader perspective and caveats
– Execution versus strategy: If AI exposes that much day-to-day agency work is executional, agencies should reallocate effort toward strategy and measurable client value.
– Guardrails and ethics: Agencies should define where AI is permitted and where it’s not, to protect the business and the client relationship.
– Not a universal replacement: AI can extend what small agencies can offer, but it’s not always appropriate to replace SaaS or experienced human specialists.
Part two teaser
This episode covered the first half of Matt’s list of ways AI can be used in an agency. The second part continues with more examples and deeper discussion of implementation, risks, and real-world stories from agencies experimenting with AI.
If you run or work in a WordPress agency and want to move beyond the hype, consider tracking your processes, drafting an AI vision document, and experimenting where repeatable tasks or massive data analysis present clear ROI. Use AI to extend your capabilities — but keep humans in the loop where trust, judgment, and customer experience matter most.