Machine Learning Outsourcing: Statistics, Pros, Cons, Advice
Content Map
More chaptersAs human life improves, customers’ demands and expectations for a certain product and service are no longer based solely on good quality. Rather than an option, quality assurance is a must for any project seeking success. The competitive market in this current landscape requires business owners to adapt quickly to new technologies to continue to attract target customers and generate profits.
After the rise of ChatGPT, artificial intelligence and its subfields, such as machine learning, natural language processing, computer vision, etc., have become some of the hottest technologies of all time. In 2023, the AI app sector reached a whopping $1.8 billion in revenue and is predicted to grow tenfold, reaching $18.8 billion by 2028. Statistics never lie.
However, where should you start your machine learning development process when such tasks require extensively specialized expertise? More than 94% of organizations use some form of IT outsourcing. Should you partner with machine learning outsourcing providers like others? Find your answers in the article below.
Machine Learning and Outsourcing Statistics
AI apps with various functions are on the rise, highlighting the growing significance of the global machine-learning market in the current landscape. Due to the explosive popularity of AI technology and its offshoots, the demand for machine learning specialists is also increasing at a dizzying pace. As recruiting personnel to implement machine learning tasks becomes too competitive, many business owners choose outsourcing as the optimal solution. Let’s take a look at some outstanding figures about AI, machine learning and outsourcing:
- The machine learning market size is projected to reach US$79.29bn by the end of 2024. (Statista)
- 83% of business owners believe that AI development is a strategic priority for their companies. (Cisco)
- 75% of executives say that AI technology will allow them to move into new businesses and ventures. (Cisco)
- AI algorithms increase leads by as much as 50%. (Harvard Business Review)
- 63% of IT specialists at large companies currently deploying AI also report that their organization is adopting generative AI. (IBM)
- 92% of G2000 companies use IT outsourcing. (ISG)
- 3 in 5 organizations turn to outsourcing for app development. (back4app)
- IT services make up around three-quarters of all global outsourcing contract values. (ISG)
- Spending on IT services worldwide in 2023 amounted to around 1.5 trillion U.S. dollars. (Statista)
Explain the Emerging Needs for Outsourcing Machine Learning
Everything happens for its reasons. Business owners certainly do not waste their budget on activities that do not bring value and profit in return. To explain the question “Why machine learning outsourcing has become popular recently,” we need to analyze two factors: one is the existing situation of the labor market, and the other is the demand of users for software products.
Rising Market Trend
AI technology is indeed a rising market trend for operational transformation. The advancement and effectiveness of AI are demonstrated through a series of breakthrough applications across different industries including gaming, entertainment, fintech, and sales, etc. Because of this excitement about AI and its related subfields, users now tend to choose and use new software that integrates artificial intelligence, rather than being loyal to traditional applications with old technologies.
Some individuals come to AI solutions due to their ability to enhance productivity and streamline processes, while others are simply curious explorers interested in the capabilities of this modern technology. Whatever the users’ purpose in approaching AI-based apps is, they both contribute to the growing interest and adoption of AI in the current landscape.
As types of software products are born to serve the needs of target audiences, integrating AI into business operations and new applications is considered one of the urgent and necessary tasks to attract and retain users, further creating a significant competitive advantage.
AI Talent Shortage
Similar to the lack of software engineers in previous years, AI talent is also in a noticeable shortage.
The strong interest of users in AI and machine learning in recent years has motivated more and more businesses to deploy this advanced technology, creating a fiercely competitive market.
As the contributions of developers and data scientists are the foundation for the success of future AI products, companies large and small are fighting over talent across the globe. However, the fast-paced advancements in AI have posed many challenges for educational institutions to produce graduates with the necessary skills, limiting the number of students who meet the requirements to graduate each year. Rapid AI adoption needs, combined with high demands for technical expertise, have led to a situation where demand exceeds supply, exacerbating the shortage.
This talent gap is one reason why many companies choose to outsource their ML projects instead of hiring a development team internally.
When Will a Business Need ML Development Services?
Lack of In-house ML Developers
With the situation in which the speed of adopting AI technology outpaces the current supply of trained ML experts, business owners around the world are competing for the same developer pool, creating a more competitive market than ever.
Like other job seekers, highly skilled AI experts often prioritize working in large enterprises with better benefits, which has caused great difficulties for startups in the same industry in attracting talent. In addition, complicated recruitment processes, which include countless different stages such as creating job descriptions, screening applicants, and conducting interviews, also contribute to the difficulty in hiring and managing in-house resources.
All of the above challenges create great motivation for the development of machine learning outsourcing models. With large available talent pools, customers using services from third parties can quickly gather dream AI development team without worrying about hiring hassles or developer shortages. The shorter the time you spend to form a team of experienced professionals, the shorter the time to market and success.
Project-based Needs Without Long-term Commitment
You cannot hire a talented person without a long-term commitment to their working environment and benefits. However, what if you only need to hire machine learning developers in the short term? In such a situation, outsourcing machine learning projects to third-party providers is one of the best solutions to consider.
Typically, a software development company offers three different hiring strategies, including dedicated software teams, IT staff augmentation, and project-based. While a dedicated team model can meet both short-term and long-term needs based on the agreement between the two parties, staff augmentation and project-based approaches are especially suitable for customers with temporary or project-specific ML requirements.
Reducing long-term obligations and ongoing employees’ benefits, such specialized methods provide clients with the flexibility to pivot or change strategies as needed. When the assigned outsourcing machine learning tasks are completed, software development contracts are immediately terminated until the next signing, if any.
Needs for Advanced AI Tools and Related Technologies
It would be a waste to invest in AI tools for just one project. However, they are indispensable tools for the success of AI products/services. Machine learning outsourcing comes into play in this situation and helps customers access advanced technology without investment costs.
To serve the professional purpose of providing machine learning services to customers in need, software development companies often invest heavily in cutting-edge technologies and software. Focusing on investing in new technologies is not only a must for such third-party organizations to serve client project requirements well but also plays a role as part of their business model to attract customers, continuously innovate, and maintain a competitive advantage.
In addition to providing support tools, outsourcing vendors with experience working with technological advancements are able to provide technical advice related to how to apply advanced AI tools to optimize the highest efficiency of the project.
Priorities for Core Competency Focus
There is no denying the importance of integrating artificial intelligence into existing products/services. However, it is often not the sole priority to sustain a business, as maintaining and improving overall operational efficiency can be more immediately impactful for a company’s bottom line. If you are overloaded with other critical business processes but still want to integrate new technologies at the same time, outsourcing your machine learning project can be an ideal choice.
By letting experts do the experts’ things, your in-house team can concentrate on core competencies and strategic initiatives without being diverted by complex machine-learning projects. Developers from software development companies with experience implementing AI models in many projects are able to protect your organization’s sensitive data, implement data analytics, and bring successful outcomes independently.
The Pros and Cons of Outsourcing Machine Learning Solutions
More and more business owners are choosing to partner with outsourcing companies to quickly access specialized skills and deploy machine learning models in software development projects instead of the complicated process of hiring themselves. Everything happens for its reasons, and business owners will not spend money on services with no value on return on investment (ROI). The positive signs of the AI outsourcing market in recent times show that this is indeed an effective solution to help customers enhance their operations and achieve their goals.
However, machine learning outsourcing also comes with limitations and challenges that require customers to be well aware before starting a cooperative relationship. What are they? Weighing its pros and cons, is AI outsourcing really a good investment? Here is a balanced look at both sides:
Pros of ML Outsourcing
- Reach a diverse talent pool from around the world
- Optimize cost factor compared to self-hiring and training
- Access to the latest AI tools and technologies
- Bring innovative and fresh perspectives to business processes
- Focus on core business operations
- Shorten development processes and faster time to market
- Scale projects up or down based on demand
- Offer ongoing support and maintenance
- Ensure smoother execution by better risk mitigation
Cons of ML Outsourcing
- Loss of control over certain project aspects
- Miscommunication due to language barriers and time zone conflicts
- Below-expectation outcomes
- Dependency on external expertise
So, Should or Should Not You Outsource Machine Learning Projects?
As mentioned above, integrating AI is not always the top priority in all cases, but the potential benefits of this technology and its subfields, like machine learning, are undeniable. ML opens doors for a variety of advancements, including automation of routine tasks, personalized customer experiences, and improved operational efficiency.
AI development is gradually becoming a new market trend, reforming all processes across different industries. However, do not rush into this path just because of the FOMO (Fear of Missing Out) phenomenon without being prepared in terms of economic potential, strategy, and data. An AI project without such a foundation can easily fall into inconsistency during implementation and lead to wasted resources.
In case you have all the above factors and have an available AI development team with the necessary AI expertise like data analysis, that is great. On the contrary, in case you lack experienced AI developers, but have little to no time for complex hiring processes, partnering with a software development company like Orient Software would be an optimal choice.
No more hiring hassle. You can start your machine learning outsourcing journey right away with our team of dedicated experts who cater to your specific requirements. Whether you want to assemble a dream team to build a new AI product or integrate AI technology into existing software and processes, Orient Software can fully meet your needs and deliver quality outcomes. Contact us for more details on our pricing models.
