Outsourcing in the AI Era: What to Delegate and What to Keep In-House?

My friends often ask me these days, "AI is so powerful now; do we still need to hire software outsourcing companies?"

The answer is: More than ever, but what you outsource has completely changed.

In the past, hiring a software outsourcing company meant hiring a team of engineers to write code. As AI drastically lowers the cost of coding, that logic no longer holds. For the same budget, you shouldn't just get "more features"; you should get better judgment + AI acceleration + a complete redesign of your processes.

It breaks down clearly into three categories:

1. No need to outsource – Things you can do yourself with AI.
2. Outsource when necessary – Projects where doing it yourself isn't cost-effective, but data ownership is critical.
3. Process consulting outsourcing – If you aim to gradually transition daily tasks to AI agents.

1. No Need to Outsource: Do It Yourself with AI

Many tasks that previously required external vendors can now be handled internally using AI tools, eliminating the need for outsourcing:

• Static website pages: Landing pages, product introductions, event pages – AI can generate these directly, allowing internal marketing teams to own them.
• Things adjustable with a prompt: Rewriting copy, changing images, tweaking layouts, adjusting colors. Tasks that once required queuing up engineers can now be done with a single command.
• One-off small systems: Event registrations, internal surveys, short-term submission forms – temporary tools that don't require long-term maintenance can be assembled with AI and existing templates.
• First draft of operation manuals / FAQs: AI writes the draft, humans refine it.
• Small bugs with clear error messages: AI can often resolve these in about 10 minutes.
• Small-scale, non-critical data conversion: Organizing Excel into CSV, field mapping. However, important data (customer, financial, ERP master) must always be manually reviewed.

The prerequisite is that your company first identifies an employee who understands AI applications – they don't need to be an engineer, just capable of using AI to complete the tasks listed above. Without such a person, all "do-it-yourself" options will stall, eventually leading back to outsourcing.

Looking at the bigger picture, this isn't a "find one person and you're done" situation. Every department needs to gradually identify individuals who can integrate AI into their workflows: marketing, sales, customer service, HR—each needs such a person. AI isn't just for the IT department; it's a tool for all departments.

2. Outsource When Necessary: Systems that Run Daily and Accumulate Data

The remaining 90% of your budget should be spent on things AI cannot do. From a data perspective, business owners need to identify which company data will be valuable in the future – these are the candidates for custom outsourcing.

Data is essential to feed AI agents: HR resignation data can power talent retention predictions, CRM conversation history can feed customer service agents, and expense reports can enable anomaly detection. Without data, an agent is an empty shell – thus, "who owns the data" is more critical than "what the system looks like."

In the past, the following three paths were flawed from a data perspective:

• Hard-to-maintain in-house team: Data ownership ✓, but the cost of maintaining staff (NT$1-2 million/year) is prohibitive.
• Complete outsourcing: Data ownership ✓, but small projects often receive disproportionately high quotes.
• General SaaS: Inexpensive, but data is locked in their system – exporting, API access, and feeding AI are all hindered. In the AI era, your data is your most valuable asset ✗.

Most SMEs end up "making do with Excel + Google Forms," leading to scattered data on everyone's hard drives, making it unusable even for themselves.

AI changes the economics: outsourcing leverages AI to lower quotes, reduce maintenance costs, and accelerate assembly with low-code. Keep core systems in-house, outsource operational systems for custom development, but ensure all data remains in your control – this is the division of labor in the AI era.

3. Process Consulting Outsourcing: Gradually "Agentifying" Your Workforce

This is what business owners should prioritize thinking about – the true game-changer in the AI era is: gradually replacing what your human workforce does with AI agents. Compared to building another website or custom system, the long-term ROI of this approach is orders of magnitude higher.

Why This Has the Highest Long-Term ROI

Because workforce agentification is a compounding investment – each automated process permanently upgrades the company's productivity, eliminating the need for the same human effort. Building a website or CRM is a one-time investment; agentification is a long-term compounding gain.

Redesigning business processes used to be difficult – it required an entire team (consultants + PMs + engineers), which was unaffordable for SMEs, forcing them to settle for Excel + manual labor.

In the AI era, it's different: AI agents + off-the-shelf SaaS assembly + low-code reduce team size and shorten timelines, making it feasible for SMEs.

Moreover, AI merges "consulting" with "IT companies" – previously, one produced PPTs and the other wrote code, with translation loss during handoff; now, a single company can handle discovery → design → implementation → launch. Essentially, you are buying a product manager (PM) who understands business processes – what SMEs truly lack is not engineers (AI fills this gap) nor strategic consultants (PPTs don't go live), but this person.

How It Differs from General Software Outsourcing

	General Software Outsourcing	Process Consulting Outsourcing
You are buying	A system (website, CRM, backend)	Business process redesign + agentification
At the start	You provide specs, vendor begins work	Consultant first discovers your business, then decides what to do
Suitable for	Knowing what to build	Knowing there's a process problem, but not what to build
AI Era ROI	Medium (scope reduced)	High (unlocks previously unachievable tasks)

4 Things to Look for When Choosing a Process Consulting Outsourcing Partner

#	What to Ask	What You Want to Hear
1	How do you conduct discovery?	A concrete workflow, not just handing you a questionnaire.
2	How do you agentify processes?	Specifics on how agents and humans interact, how permissions are set, who judges errors.
3	What AI tools do you use? Can we take over afterward?	Mainstream, stable tools that don't lock you in.
4	How do you support us if we want to make changes after launch?	Comprehensive documentation, transition support, long-term partnership.

Warning: Do not force process problems into a general software outsourcing contract – the vendor will build you a system that "precisely matches the specifications but fails to solve the real problem."

Conclusion

Outsourcing in the AI era is not a cost-saving tool; it's a lever to amplify organizational capabilities.

Business owners' thought process should be simple:

1. Avoid outsourcing if possible (handle tasks internally with AI).
2. Internal organization needs an AI team: Not just the IT department, but every department needs to identify individuals who can integrate AI into their workflows.
3. Gradually agentify your workforce: Find a process consulting outsourcing partner who can implement AI within your organization and improve processes long-term – this is the true opportunity in the AI era.