Build or Buy: Exploring AI Solutions for Business

Guest Post by Tushar Kulkarni, CEO, Big Kitty Labs

Artificial intelligence is transforming how companies operate, compete, and create value. Yet for many leaders, one strategic question continues to surface in every boardroom, planning session, and budget cycle:

Should we build our AI solutions in-house, or should we buy and integrate existing platforms?

It is one of the most important decisions a business can make today, because it shapes everything downstream—speed of adoption, cost, capability, talent strategy, security, and long-term competitiveness. At Big Kitty Labs, we’ve spent the past decade building custom software, automation frameworks, and enterprise AI systems across industries. We’ve watched this decision become both more urgent and more nuanced as the technology landscape evolves at unprecedented speed.

Here’s how leaders can approach the “build vs. buy” conversation with clarity and confidence.

1. Start With the Problem, Not the Platform

Many organizations jump too quickly to a tool—an LLM, an off-the-shelf chatbot, an automation product—without fully defining the business challenge they’re solving.

Before discussing solutions, ask:

• What measurable outcomes are we trying to create?

• What workflows, user groups, or pain points are involved?

• What data do we need to unlock or integrate?

• How will success be defined six and twelve months from now?

When your problem is clearly defined, the right approach—build or buy—often reveals itself.

2. When Buying Makes the Most Sense

Leaders should lean toward buying an AI solution when the goal is:

Speed to Value

If you need something operational in weeks rather than months, existing tools—CRM copilots, support automation, analytics copilots—can shorten time to deployment dramatically.

Standardizing a Common Use Case

Many AI use cases are widely shared across industries: customer support, sales workflow automation, document extraction, forecasting. Vendors have already optimized for these patterns.

Reducing Technical Lift

Buying can be especially attractive when internal teams are stretched thin or when the initiative isn’t central to your competitive differentiation.

Accessing Built-In Compliance and Security

For regulated industries, a reputable vendor’s compliance posture may be stronger and more cost-effective than building your own.

3. When Building Is the Better Investment

Sometimes, buying creates more constraints than value. Building is often the right choice when:

AI Directly Impacts Competitive Advantage

If the use case is uniquely tied to how your business wins—your product, your service model, your data advantage—it may require custom design.

Off-the-Shelf Tools Don’t Fit Your Workflow

AI becomes powerful when it integrates deeply into your systems of record, your customer experience, and your operational processes. Custom build ensures this.

Your Data Is Your Differentiator

If you have proprietary datasets, historical insights, or unique operational signals, a custom solution can unlock value no vendor can replicate.

Scalability and Extensibility Matter

Building allows you to design for how the system must grow over time—new use cases, new integrations, new levels of automation.

4. The Hybrid Model: A Practical Path for Modern Organizations

One of the biggest misconceptions in AI strategy is that organizations must choose between building and buying. In practice, the most successful companies are doing both.

A hybrid AI architecture allows you to:

• Use pre-built copilots to accelerate adoption

• Develop internal components that encode your unique strengths

• Layer custom logic, integrations, guardrails, and workflows on top of vendor tools

• Evolve into an AI-enabled operating model without a full rebuild

This balanced approach also protects organizations from vendor lock-in and helps teams build internal AI literacy while delivering immediate business results.

5. The Real Decision: Are You Building an App or Building Capability?

The deeper strategic question isn’t just “build or buy.” It’s:

Do we want to build an AI application, or do we want to build an AI capability?

Buying a tool solves a problem.
Building a capability transforms the organization.

Leaders who treat AI as a capability—supported by data infrastructure, governance, experimentation, and training—gain long-term resilience and a true competitive edge. Those who only chase point solutions risk fragmentation, duplication, and missed opportunity.

6. How Big Kitty Labs Helps Organizations Navigate the Choice

At Big Kitty Labs, we work closely with enterprise and mid-market teams across industries to clarify strategy, architect solutions, and implement with speed and precision.

We help organizations:

• Determine when buying is the fastest and most effective approach

• Evaluate vendors, platforms, and total cost of ownership

• Identify high-value opportunities where custom solutions unlock unique value

• Build hybrid strategies that blend tools, integrations, and custom workflows

• Create sustainable AI roadmaps that evolve with the business

• Train teams to adopt and extend AI solutions confidently

AI adoption doesn’t have to feel overwhelming or risky. With the right strategy, it becomes a force multiplier for every part of the business.

Final Thought: AI Is Not a Project—It’s a Transformation

The organizations that thrive in the next decade will treat AI not as an experiment, but as a system-wide enabler for growth, efficiency, and innovation.

“Build or buy” is an important question.
But the most important step is getting started.

About Big Kitty Labs

Big Kitty Labs is a leading software innovation firm specializing in AI, automation, product development, enterprise systems, and technology acceleration. We help organizations move from ideas to execution with speed, clarity, and impact. Learn more at bigkittylabs.com.

About the Enterprise Technology Association

The Enterprise Technology Association is the nation’s fastest-growing network for leaders in AI, cybersecurity, cloud, and emerging technologies. ETA drives education, enablement, and ecosystem building through AI Week events, Intelligent Regions initiatives, certification pathways, and national leadership programs. Learn more at joineta.org.