The hidden costs and complexities of building AI for service

When it comes to AI agents, companies are once again grappling with the age-old question: should we build it ourselves? And it’s easy to see why— off-the shelf foundation models are everywhere and for many, building your own ML pipeline and end-to-end AI-powered chatbot application feels like the only way to keep control.

But just because you can do something doesn’t always mean you should. For most companies, building AI for service brings added costs, risks, and complexities that are easy to underestimate.

The decision itself can slow progress—62% of CX leaders say it’s stalling their AI adoption altogether. And while you’re stuck debating, or buried in development cycles, your competitors are already resolving issues faster, scaling more easily, and cutting costs with purpose-built solutions.

The appeal of DIY agents—and what companies often miss

Everyone wants a solution they can control and customize, but building from scratch isn’t the only way to get there.

More often than not, custom AI actually impedes flexibility with more constraints, slower timelines, and unexpected challenges. This can be true for even the most capable of teams because there are hidden complexities in building AI for service that often escape early detection, only to show up much later in the process. Agentic AI in particular is a nascent field where best practices are just starting to emerge – smaller inhouse teams can struggle to keep up with these changes.

Here’s just a snapshot of what you’ll need to consider:

• Heavy engineering overhead: Building the logic, integrations, and fallback rules from scratch requires sustained engineering effort. But it doesn’t stop there, your most expensive engineers may find themselves spending time debugging bot behavior instead of building new features. Without no-code controls, teams can become overwhelmed by constant tuning requests and support escalations.

• Non-deterministic systems: Unless your teams are well-versed in building and maintaining AI systems, they’re in for a real surprise when faced with research cycles that don’t fit nearly into classic development timelines, rendering estimations meaningless, or when experiencing sudden performance drops as the system experiences model drift.

• Orchestration trap: Agentic systems are all about building specialized autonomous AI agents that work together to resolve the most complex problems. Each of these can require a dedicated team, and designing orchestration logic that governs how they interact is a tough challenge even for fully dedicated AI companies.
• Integration drag: Custom connectors, brittle APIs, versioning issues—what seems simple upfront can quickly turn into a months-long integration problem when systems don’t cooperate.
• Safety, security, and compliance liability: Responsibility for safety, security, and compliance falls on you. From bias mitigation and privacy controls to hallucination prevention and confidence scoring, none of it comes standard. You’ll have to define, build, and govern it all. Not to mention the risk of prompt injections and malicious actors gaining access to your systems through your custom bot.
• Measurement burden: DIY AI means building your own evaluation, benchmarks, feedback loops, and tuning processes just to understand what’s working best.
• Edge case responsibility: Doing it yourself means owning every AI misfire, misunderstanding, and “I didn’t mean that” escalation. These edge cases will multiply as you scale.
• Ongoing cost and complexity: This isn’t a one-time build. You’re now on the hook for tuning, orchestration, hosting, security, and updates—costs that are often underestimated and rarely go away. Every AI system becomes more expensive the more you scale, and LLM providers will only give you discounts above volumes that even large enterprises can hardly achieve.

Why building with Zendesk is a better business move

Service teams are operating in a world of rising expectations and tighter budgets. There’s little margin for error and big consequences for falling short. That’s why partnering with a proven, purpose-built platform can help you move faster and free up resources with far less risk.

Here are just a few of the reasons that companies choose to partner with Zendesk rather than going it alone:

Built into the only Resolution Platform for service

• Zendesk AI Agents, Copilot, QA, Knowledge, and Analytics all run on a single Resolution platform.

• Orchestration is already an integral part of the system, integration is guaranteed—it’s built to resolve and it starts working immediately.

Customizable with full control

• Customize workflows, triggers, and escalation logic without engineering effort.

• Add global instructions that govern and customize the behavior of your AI agent.

• Edit the behavior of our AI systems to adapt to various customer segments you can define on your own.

• Zendesk gives admins full control and visibility into how and when our AI systems act, with no dev time required.

Native integrations, no duct tape required

• Connects directly to your CRM and knowledge base.

• No need for middleware, patchwork, or API gymnastics.

• Set up any workflow across human and AI with Action Builder

Everything works on day one

• Launch in three-clicks without training or dev work. Scale seamlessly across messaging, email, voice, and more – in over 80+ languages.

• Bring and use any of your Zendesk or external data source to implement generative replies.

Resolution quality improves over time

• Built-in QA scores 100% of interactions across human and AI agents. Continuous insights and optimization happen automatically – no manual effort, and no data scientists required.

Certs, controls, and compliance already done

• HIPAA, SOC 2, GDPR, and ISO 27001 support come built in.

• Zero sharing by default.

Guardrails come standard

• Includes confidence scoring, fallback logic, audit trails, and more, so you don’t have to build your own safety net.

Billing only kicks in when it works

• Only charged when AI fully resolves the issue.

• You don’t pay for failure, orchestration, or hosting.

Continuously tested, monitored, and improved

• AI performance is regularly benchmarked across use cases so you can trust it’ll work without burning cycles to prove it.

• New models, like the latest GPT-5, are evaluated, tested, and deployed in under 24 hours. Every decision is documented and auditable, ensuring transparency and reliability as our AI capabilities evolve.

For companies already partnering with Zendesk, our deep expertise is driving notable results. Learn more from Hello Sugar and Phonero.

Stay focused on what sets you apart

Even well-resourced teams often struggle to match the speed and scale of a platform that’s purpose-built for service—especially when time-to-value matters.

So why start from scratch? Zendesk AI is trained on billions of real-world service interactions and built right into the only Resolution platform for service. That means AI agents backed by our nearly 20 years of industry expertise come fully integrated into your service stack—working hand-in-hand with your ticketing, knowledge, QA, and analytics starting day one.

In the end, the smartest move isn’t to build everything. Put your energy into what makes your business unique, and partner with us to deliver exceptional AI-powered service.