Keys to using IT outsourcing for machine learning and AI projects

Companies are increasingly aware of the potential that tools such as machine learning and artificial intelligence offer to optimize processes, improve decision making and offer more personalized products and services. However, a recurring barrier to the effective implementation of these technologies is the shortage of qualified and experienced personnel in both fields. This demand far outstrips supply, making it difficult for companies to find suitable talent and carry out ambitious projects in these areas.

Furthermore, in many cases, companies' internal technical teams may lack the necessary specializations to develop and implement machine learning and artificial intelligence solutions effectively. Training internal staff can be expensive and time-consuming, delaying project progress and decreasing the company's competitiveness in a market that demands constant innovation.

Faced with this situation, many companies are turning to IT outsourcing as a viable solution. By outsourcing these tasks to specialized suppliers, companies can cover the lack of qualified personnel more quickly and at a price appropriate to their budget. This modality not only allows them to access specialized talent immediately, but also significantly speeds up the development of their projects, giving them a competitive advantage in a constantly evolving business environment.

"There is concern that 'the rise of the machines' will replace human workers, but we should look at how people and machines can work collaboratively as co-bots," said Deloitte CEO Cathy Engelbert. "The ability to leverage new technologies to modernize our workforce will ultimately lead to new opportunities to develop high-value skills for our workers".

Signs that indicate your business needs an AI solution

• Need to automate time-consuming manual tasks

Your work team may be the most competent and helpful, but monotonous and repetitive tasks can make your employees tired, feeling that they can take advantage of their time on more strategic tasks. In these cases, there are artificial intelligence solutions that can be very useful in terms of automating repetitive tasks.

“While these AI platforms do not completely replace humans, they dramatically improve document-centric processes, allowing employees' time to be spent on more satisfying work while increasing an organization's revenue by speeding up time. of obtaining value to achieve business objectives”, they added on the subject in an article in Business Reporter magazine.

• Fact Check

“In an era of strikingly realistic deepfake videos, sophisticated manipulation of the news and social ecosystem to influence elections, and growing concerns about misinformation, the line between fake and real continues to blur. “AI advances can help fact-checkers with pattern analysis, context clustering, and social signal processing to restore trust, quality, and transparency of information for all”, they noted in an article in Forbes.

• Frauds

In the case of digital banking platforms or electronic commerce, a latent concern is fraud. Cybercriminals try different maneuvers every day to try to steal customer data while they make their financial transactions online. And AI has become the most agile and efficient tool to combat this situation.

“For example, companies like Sift Science and Feedzai leverage artificial intelligence and machine learning algorithms to classify and evaluate data in a matter of seconds. As a result, these companies have greatly reduced fraud, spammers, and a wide range of financial crimes. Other companies like PoshMark, Door Dash and others have been able to reduce fraudulent transactions, chargebacks and customer spam”, they added in a specialized article in Entrepreneur.

Signs that indicate it's time to implement machine learning tools in your business

• You do not answer your clients' questions on time

In this scenario, implementing a chatbot is a more than opportune decision. “These aptly named software programs use machine learning and natural language processing (NLP) to mimic human conversation. They work with pre-programmed scripts to involve people and answer their questions by accessing the company's databases to provide answers to those queries," they explained on the subject on the specialized portal Tech Target.

• The amount of data that must be processed is abundant

If your business is generating a significant amount of data, such as customer transactions, inventory records, or sensor data, machine learning can help extract valuable insights and make more informed decisions.

• You need a mechanism for detecting complex patterns

When companies are facing challenges that involve detecting complex patterns in large data sets, such as predicting market trends, identifying anomalies, or optimizing processes, machine learning can offer solutions that go beyond conventional approaches.

Keys to using IT outsourcing in AI and machine learning projects

Selection of specialized suppliers

Look for outsourcing providers with specific experience in AI and machine learning projects. Make sure they have a proven track record of successfully delivering similar projects and have a team of experts in these areas.

Definition of roles and responsibilities

Clearly establish the roles and responsibilities of each party involved in the project. This includes identifying who will be the main point of contact in both organizations and who will be responsible for different aspects of the project, such as data collection, modeling, evaluation of results, among others.

Risk management

Proactively identify and manage potential project risks such as delivery delays, changing requirements, data quality issues, and more. Work closely with the outsourcing provider to develop contingency plans and minimize the impact of risks on the project.

Training and knowledge transfer

Ensure your internal team receives the necessary training to understand and maintain the solutions developed by the outsourcing provider. Additionally, encourage knowledge transfer between the internal team and the outsourcing team to ensure a smooth transition once the project is complete.

By following these keys, you will be able to make the most of IT outsourcing on AI and machine learning projects, maximizing efficiency, quality, and overall project success.

Do you need an IT outsourcing provider for your next AI and machine learning project? At Rootstack, we have +14 years of experience supporting companies in their digital transformation. Contact us.

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