The biggest dilemma for a business is to choose between building an in-house team and outsourcing the AI project to an offshore expert. We’ll discuss the benefits of outsourcing in detail to understand why it is the preferred choice for most enterprises.
Artificial intelligence has been a game-changer for many small, medium, and large enterprises. It has made digital transformation possible by helping businesses use data to derive actionable insights and make better decisions. AI can be used in different verticals in the organization.
For example, AI applications help the sales team with demand forecasting and market trend predictions. Artificial intelligence is used by the human resource department for recruitment and tracking employee performance. AI has a role in supply chain management, finance, transportation, and customer service.
According to Gartner, organizations using AI for customer service are expected to see a 25% growth in customer satisfaction by 2023. More than 90% of the leading business organizations are investing in AI. In fact, 86% of the CEOs considered AI the mainstream technology in their offices as of 2021.
This raises the question of whether you need to hire an in-house team for AI projects or outsource the responsibilities to offshore AI developers in India. Outsourcing has its benefits and is a preferred choice for many businesses.
Small and medium-sized businesses outsource to avoid infrastructure and maintenance costs. Large enterprises outsource to increase employee productivity. Around 70% of the projects are outsourced to reduce the budget. Flexibility is the second next reason for outsourcing. Read on to understand how artificial intelligence can help your business and why outsourcing AI projects is beneficial.
Artificial intelligence is becoming an imperative part of several businesses because of the range of advantages it offers. How you use AI within the business determines the results. Here are a few important areas where AI is prominently used by leading organizations.
Automation is the process of using technology to complete repetitive tasks that are otherwise handled by employees. It reduced workload to save time and energy. It reduces the risk of human error and delivers more consistent results in less time. Machine learning algorithms are used for automation in various industries like healthcare, manufacturing, retail, entertainment, etc.
The sales team has a lot of responsibility. It has to predict the market trends, understand customer behavior, identify the right time for the promotional campaigns, and align everything with the business goals. AI application will simplify their job while empowering them to use the insights to plan marketing strategies more effectively.
Inventory management, warehouse management, and aligning the movement of stock from the warehouse to the stores or transporting it to the distributors require constant coordination with internal and external teams. A small miscommunication at any stage of the supply chain can lead to delays and losses. Artificial intelligence prevents this by predicting delays in advance and sending automated alerts to supervisors.
Data is available in abundance in today’s world. Enterprises can gather data from several external sources. But how you use the data determines the success of your business. You need the right tools to clean, structure, process, and analyze data to get accurate insights. AI streamlines this process and also provides insights in real-time. You can use the latest data from the market to make decisions instead of relying on outdated information.
Using AI tools will give you an edge over other businesses in the same industry. It helps small and medium-sized businesses establish themselves in the market despite the strong presence of global enterprises. Artificial intelligence is ‘the key’ you need to survive competition, capture markets, and expand your customer base.
Having learned how AI can help your business, you should decide between building an in-house team and outsourcing the projects to AI consulting companies in the market. It might appear tempting to start from scratch and develop an in-house team so that you will always have someone working on the AI tools.
However, you should consider the following aspects before going ahead with a permanent team within the enterprise.
Despite the increasing demand for AI and ML engineers, data scientists, etc., there aren’t enough professionals to bridge the gap between demand and supply. In such instances, hiring talented and experienced professionals in a short time is almost impossible unless you are a leading global organization.
Furthermore, there’s no guarantee that the professionals will stay with your business. They can move to another company if they get a better offer. This means you have to start the recruitment process once again. It will lead to more delays and cause a waste of valuable resources.
The cost of having an in-house team doesn’t end with recruitment. You have to pay salaries and provide the necessary infrastructure and resources for the team to work on the AI projects. You also have to deal with the cost inflations due to additional requirements/purchases, pay hikes, and losses if the project is not successful.
An in-house team is expensive for a business unless you have the budget to sustain an R&D department and invest millions into it regularly. Machine learning outsourcing will cost less and deliver faster results.
The in-house cannot work in isolation. It needs input from other departments and should have team members for the same. However, not every business has enough manpower to spare employees from one department to work in another. Asking the employee to handle everything will lead to stress and decreased productivity.
Quality data is the key to accurate AI models. The algorithm will deliver results based on the input data you provide. But where does quality data come from? Data available online cannot be directly used to train models. It needs to be cleaned, formatted, structured, and processed before being fed into the model. The in-house team will spend most of the time cleaning the data rather than training the ML models. The data will be out of date by the time it is used for analytics.
This is the main drawback of having an in-house team to work on artificial intelligence projects. You never know what could go out of place and cause a delay with the project. The top management and the employees also have to handle day-to-day decisions to keep the business going. The AI model may not work with the latest technology if you spend years working on it. The model will be outdated even before you use it.
Artificial intelligence outsourcing is the solution to various challenges you have to face when dealing with an in-house team. You get direct access to experienced AI developers and engineers without spending time and money on recruitment. The developers will work on your AI project until it is complete.
There’s a huge demand for AI and ML engineers and data scientists in the current market. Reports show that the demand will continue to increase over the next few years. However, there aren’t enough experienced professionals to take up the jobs. You can find someone for the entry-level job (a fresher) but hiring an expert is still a challenge.
That said, many such experts are working with consulting companies and starting their own businesses to offer outsourcing services. When you choose a sound service provider, you are handing over the AI project to someone capable, efficient, and talented. You can directly interact with them and stay in the loop as they work on your project.
The service provider will already have the necessary infrastructure to work on your artificial intelligence project. You don’t have to spend money establishing the environment and providing the necessary resources to the team. Furthermore, the consulting company will build an AI team depending on the complexity of your project.
You just have to share the project details, your requirements, and additional specifications. The amount you pay an outsourcing company will be much less than what you spend on developing the AI model from scratch. You are hiring their expertise as well as their infrastructure and resources.
Consulting companies are good at what they do because it’s their domain and day-to-day work. The professionals would have worked on numerous AI projects from different industries. They also have all the required tools within reach. Once they plan and divide the project amongst the team, they don’t have to wait for anything else.
It is easy for them to identify the errors during the development stage and make changes to the code/ framework/ environment as and when necessary. Moreover, consulting companies know that delays can affect their reputation. They deliver work as per the schedule.
AI and data science service providers put extra effort into creating reliable and accurate algorithms for decision-making. They gain access to tools and sources that minimize the risk of algorithm bias. This reduces the chances of creating a flawed AI model.
Unlike the in-house team, the offshore service provider doesn’t have to work with limited resources or data. They can expand their reach and usually have a wider setup to cater to businesses from different domains. Outsourced projects have a lesser chance of failing or delivering skewed results.
Managing big data is no small feat. You need a data warehouse or a data lake to store all the collected data. You have to create a streamlined data flow within the enterprise by connecting the systems and integrating them with third-party tools/ applications.
Then, you have to continuously clean and analyze the data. You also have to take additional care with sensitive data and ensure ample data security to prevent breaches. This can severely affect your budget and put excess pressure on existing employees. Outsourcing solves the problem as the responsibility falls on the experts.
Outsourcing companies offer more than one engagement model to work with clients. You can collaborate with the team or hire them as a temporary internal team until the project ends. The team is created based on the project’s requirements and deadline.
For example, if you want to complete the project soon, the consulting company will build a bigger team to work on it. The team will work with your business according to the engagement model you decide. The decision-making power can lie with you or the team. Outsourcing doesn’t always mean that you don’t have a say in the project anymore.
Of course, we know that every outsourcing company is not the same. Outsourcing is beneficial when you hire the right company for your artificial intelligence projects. That requires some research and effort from your side. Take into account the following factors when choosing a suitable AI consulting company to work on your projects.
What is the work experience of individual team members? The consulting company may be relatively new, but the experts should have some working experience in the relevant domains.
When choosing a business intelligence outsourcing company, make sure to look at the project portfolio. Can the company handle diverse projects? Do they offer expertise in more than one field?
How do you communicate with the outsourcing team? How is their response? Do you get timely replies? Are they open to explaining and providing more information?
Does the company’s working methodology align with your business goals? Can you work together on the AI project without worrying about the results?
Does the company offer a flexible pricing model? Did you compare the charges with the market rate? Keep in mind that a company might charge more upfront and not add any hidden costs at the last minute while some consulting companies have hidden charges.
Does the company offer detailed documentation of the project for future reference? That way, you don’t have to approach them for every small issue but can solve it on your own.
Know what the previous and existing clients have to say about the consulting company. Talk to a couple of them personally before finalizing a service provider.
AI outsourcing services are used by several MSMEs and large enterprises because of the benefits we listed above. In today’s era, it is really required to stay up-to-date and relevant to survive market competition.
Outsourcing AI projects to reputed consulting companies will give you the necessary foundation to establish your business for the long term. Let the AI offshore service provider take care of the AI and ML models while you zero in on the core aspects of your business to increase ROI.