Why More Companies Are Turning to Artificial Intelligence Outsourcing in 2025

Cost Efficiency

A key reason for outsourcing AI is cost savings. For better context, let’s consider the financial requirements involved in building an in-house AI team, including recruitment, salaries, training, and infrastructure. The recruitment process is often lengthy and costly. With the ongoing talent shortage, there is no guarantee you will secure the talent you need, especially specialized talent. This is not to mention that an AI developer’s salary can go up to $120,000 to $150,000 a year.

Outsourcing significantly reduces costs involving labor, training, and infrastructure. The reduction of costs, in this case, goes hand in hand with risk mitigation. Instead of having a fixed spending on an in-house team that doesn’t ensure financial success, outsourcing AI gives you the flexibility to choose pricing models and the ability to align expenses with deliverables.

Once your AI services are in place, you can leverage its subsets, like Natural Language Processing (NLP), Machine Learning (ML), and Intelligent Process Automation (IPA) to automate repetitive tasks, analyze data for predictive maintenance, and handle routine questions to save even more costs in the long run.

Faster Time-to-Market

Speed to market is crucial, as it allows you to:

• Present the product to customers before your competitors, gaining market advantage.
• Adapt and respond quickly to the changing customer preferences and market conditions.
• Build credibility and a strong reputation. This is especially vital as only 55% of products are launched on schedule, according to Gartner.

Outsourcing provides you with the expertise and tools to push time-to-market. For instance, according to McKinsey research, a multinational hotel chain outsourced the development of its software applications, resulting in a 25% shorter time-to-market.

Outsourcing companies typically have tried-and-true software development processes and frameworks. By having a professional partner handle all the legwork for you, your in-house team has the time and resources to take care of core, value-driven business activities.

Ensure The AI Algorithms’ Reliability

Experienced vendors have the right capacity and expertise to work with predictive decision-making algorithms. There have been several controversies surrounding AI algorithms, including bias, privacy, transparency, and misuse. Make sure your business partner is aware of such issues. For a more reliable AI algorithm, there are several steps you can take:

• Your AI system should be trained on datasets that are authoritative, free from biases, and representative of real-world scenarios.
• Involving domain and technical experts in AI testing and validation when you can. This ensures AI meets end users’ specific needs.
• AI should be developed and deployed with strict security measures like encryption, authentication, and regular auditing.
• Ethical considerations, particularly data privacy and bias avoidance, should be addressed early on to build confidence and ensure inclusivity.

Focus on Core Initiatives

AI outsourcing allows in-house teams to focus on what they are doing best, whether it is drafting compelling marketing campaigns, market expansion, or customer service. Instead of spending time on recruiting, training, and building the infrastructure, your team focuses on its core expertise. Outsourcing the creation of AI systems doesn’t necessarily mean having no in-house team at all. Striking a balance between internal teams and outsourced teams, for many companies, is how they achieve the most benefits.

Enhanced Decision-Making

AI goes beyond automating rule-based, mundane tasks. Leveraging AI allows you to analyze a large amount of historical data, patterns, and customer behaviors, enabling confident, data-based decisions.

Forbes reported that 75% of CEOs say AI will empower them to enter new markets and endeavors, and 83% of executives think AI is now a strategic priority for their companies. Many businesses have already embraced AI in business operations.

How AI is utilized, however, often depends on a business’s industry. Let’s take Shell, a multinational oil and gas company, as an example. The organization has used AI to analyze a massive amount of data for oil drilling placement. It also uses AI technology to analyze data from its existing oil drilling equipment for predictive maintenance, preventing equipment failure or maintenance needs early on.

Boosting Innovation

In addition to improving the existing systems, AI has the power to facilitate innovative ideas. With AI, especially Generative AI (another subset of AI), you can easily generate new text, images, music, and other forms of media. This is on top of what AI can already do, including optimizing operations, speeding product development, and suggesting novel methods to meet customer expectations.

All in all, AI opens the doors to endless and exciting possibilities, untapped market niches, and innovative solutions to elevate your business to the next level.

Software Development

Software development is one of the most common use cases for AI outsourcing. Many turn to third-party vendors to integrate AI into their development processes. This might involve automatic code completion, debugging and error detection, code optimization for better readability, and checking for industry compliance.

For example, did you know that tech giants Microsoft and Meta let AI write up to 30 percent of the code in their projects? Meta’s CEO, Mark Zuckerberg, even predicted that AI will be able to handle up to 50% of the organization’s work within a year. Outsourcing AI capabilities, especially when a company lacks AI expertise, is a smart strategic move to stay competitive.

Outsourcing teams can also use AI to build machine learning models and deploy automation tools that meet their unique needs. Using AI in software development allows the team to build faster and scale better.

Data Analytics

AI has the power to analyze a massive amount of data in a short time, allowing businesses to make confident and informed decisions. Every industry benefits from data analytics, as it uncovers patterns in customer behavior, identifies trends, predicts outcomes, and gauges customer satisfaction.

Outsourcing AI partners can help you incorporate the technology into the data analytics pipeline. Depending on your business’s specific needs, AI for data analytics can be tailored to meet specific use cases. For instance, you can use AI data analytics to monitor software development projects, track machinery’s workability for timely maintenance, or even the workability of applications. AI in data analytics involves a wide array of activities, consisting of data collection, data cleaning, data analysis, data visualization, predictive analytics, and more.

Customer Experience

Adopting AI to enhance customer experience isn’t simply a trend; it has become a necessity. Businesses that use AI automation are able to address tickets 52% faster than those that do not. Customers often expect businesses to keep up with the latest technology to enhance their overall experience. If you still need more convincing to outsource AI services in customer service, here are four examples for your reference.

• Chatbots: AI chatbots can give customers instant responses. Built using NLP and ML, the chatbot can understand and answer common questions naturally and help customers troubleshoot problems at any time.
• Virtual customer assistants (VCAs): Think of VCAs as advanced chatbots. Beyond conversational tasks, a virtual agent can help customers place orders, handle account issues, and even offer product recommendations.
• Automatic follow-up: Have you always wanted to collect customer feedback after certain interactions, but more often than not, forget to send follow-up emails or surveys? Robotic Process Automation, or RPA, can help you with that. Ask your partner to have RPA focus on performing these repetitive but crucial tasks, and free up a significant amount of time while still keeping your customers happy.
• Quality assurance: AI can review and flag issues or violations in support conversations, so you can make timely interventions and ensure customers always receive the highest quality of service.

Healthcare

Healthcare has seen a rise in AI adoption, although its pace is still slower compared to other industries. Still, this doesn’t mean one should skip outsourcing AI in healthcare. The technology has achieved remarkable milestones thanks to AI and its related technologies.

• AI for brain scans (stroke diagnosis): Two universities in the UK have developed brain scan software that is “twice as accurate as using a standard visual method.” The software could even diagnose how long ago the stroke occurred, which is critical information for treatment.
• AI for fracture detection: Did you know that urgent care doctors miss bone fractures in up to 10% of cases? AI can address this issue effectively and reduce the number of unnecessary follow-up appointments.
• AI for early disease detection: By analyzing large datasets, AI has been able to detect and predict disease years even before any symptoms appear.
• AI for healthcare administration: Organizations have introduced tools like Google’s healthcare AI models or Microsoft Dragon Copilot to reduce paperwork by automatically transcribing consultations.

Financial Services

AI is a versatile and robust tool, especially if you are a startup. Leveraging AI is how you modernize traditional banking processes, gain a better understanding of the market, and stay competitive. With the right AI outsourcing partner, you can apply AI across a range of areas to drive real impact.

• Algorithmic trading: Financial markets and computer programming are combined in algorithmic trading to execute trades at precise times. Firms can use AI to analyze data, both historical and real-time, to make smart and fast trading decisions.
• Credit scoring: Instead of spending hours upon hours and sifting through customers’ online behavior, AI can quickly review the necessary information for credit-related decisions.
• Fraud detection: 25% of financial institutions reported fraud losses of $1 million in 2024. To prevent this, make sure your outsourcing partner deploys AI in fraud detection – by flagging unusual behaviors or suspicious spending patterns.
• Personal finances management: AI can be applied in cases for personal customers as well. Have your specialists use AI to efficiently analyze spending habits and risk tolerance to suggest personalized budgeting and spending strategies.

Compliance Management

Every industry has a set of laws and regulations that a firm must comply with. This is especially true for strictly regulated sectors such as healthcare or finance. It is crucial to accurately follow any regulations or standards, as failing to do so can result in negative repercussions such as fines or decreased credibility.

One way to handle compliance issues, other than hiring a team of experts to constantly monitor this domain, is to implement AI. Here is how AI can assist with compliance management:

• AI can efficiently handle long documents and summarize them, saving hours of work.
• The technology can automate the categorization of reports, for example, reports related to fraud, corruption, or harassment.
• When it comes to policies, employees can directly interact with AI to get quick responses with high accuracy.
• Notify teams when there are changes in regulations and facilitate changes via automated workflows.

Focus on Quality

AI software is complex, and it’s a challenge to maintain a consistent and accurate output. Hence, AI outsourcing often requires partners with a high level of expertise to not only match the standard of your industry and business but also to prevent inconsistencies in the quality of AI responses. Make sure your partner is credible and meets your criteria.

Another thing you should discuss with your vendor early is how their work will be monitored or evaluated. Talk about clear benchmarks and regularly assess the deliverables.

Data Security & Transparency

Data management is complicated when working with a third-party vendor, as workflows often require sharing sensitive data. This problem is amplified even further when you work with an offshore partner. While AI is powerful and can be used to detect threats, it also introduces various risks.

The solution? Work with a credible partner, like Orient Software. Discuss and put in place strict security and privacy policies. Make sure to invest proper time and effort into creating these policies, as they protect you and your customers’ data from malicious actors.

Regulatory Compliance

Other than data security, AI also faces an array of legal complexities. This includes copyright and ownership issues, algorithmic biases, and other ethical considerations. Even though its regulations are still under development, businesses have to navigate the legal landscape carefully. Choose a partner who has comprehensive knowledge regarding AI legal and compliance issues to minimize risks.