Artificial intelligence takes on outsourcing

Since the 1990s, many large organizations have outsourced business processes, support tasks, call-center operations, IT services and more to third parties in regions with low-cost labor — India, the Philippines and Brazil among them. Thanks to connections with high-speed data networks, this work has been done nearly as quickly as it could be in the home office, yet at far lower cost.

However, outsourcing has its issues, including compliance, cybersecurity and privacy. Some companies have responded by bringing the work back, a shift known as insourcing. And now they can use artificial intelligence to free staff from this new — and often rote — work, assigning rules-based processes to AI systems and their intelligent algorithms. We call this new development Outsourcing 2.0. 

The benefits of outsourcing work to AI

Outsourcing to AI systems can deliver a long list of valuable benefits. These systems operate with enhanced speed, accuracy and scale. For AI systems with built-in learning, performance also improves over time. In addition, some AI systems now use natural language processing (NLP) to enable intuitive communications between machines and human workers. And AI’s robust security capabilities mean an organization’s valuable data assets are safeguarded. Finally, unlike human workers, AI systems can operate 24x7.

The number of potential applications that lend themselves to Outsourcing 2.0 is greater than you might expect. Generative AI and other technologies have the potential to automate work activities that absorb fully 60% to 70% of employees’ time today, according to estimates by McKinsey & Co.

Nearly every industry, from manufacturing to retail to business services, can enjoy the benefits of Outsourcing 2.0 in some way. And as AI capabilities continue to expand, more industries and business processes will come onboard.

The changing AI landscape

Outsourcing 2.0 has been made possible by the expansion of AI research, resulting in innovations that include machine learning for analyzing large data sets to derive insights; NLP to understand and respond to human language; computer vision for classifying image and video objects; and pattern recognition for detecting scams like credit-card fraud. These new capabilities have led more organizations to use AI for more tasks.

The scope of AI applications that hold potential for picking up business process, tech help desk and customer support, and other common outsourcing functions, is immense, ranging from chatbots to personalized recommendation engines to data analytics. AI-based tools can match and even outperform humans on selected tasks while operating tirelessly at scale. As the technology continues to develop, AI will be able to augment and automate even more processes.

These and other AI innovations are leading to the technology’s growing acceptance. Major tech firms including Google, Microsoft and Amazon Web Services (AWS) now offer cloud-based AI services to jumpstart development. Fully half of organizations (50%) surveyed in 2022 by McKinsey said they were using AI, up from just 20% in 2017. In the same survey, respondents said the average number of AI capabilities their organizations use has doubled, rising from 1.9 capabilities in 2018 to 3.8 in 2022.

These advantages are leading to a large market. Market watcher IDC expects spending on AI software to grow from 2022 to 2027 at a compound annual growth rate (CAGR) of over 30%, approaching a total worldwide value of $251 billion.

The growth of generative AI has been even more dramatic. The best-known of these systems, OpenAI’s ChatGPT, was introduced in late 2022 and quickly attracted an estimated 100 million monthly users. More recently, OpenAI said that number has grown to 100 million weekly active users. 

Determining where AI fits in your business

For business leaders hoping to benefit from Outsourcing 2.0, a good way to start is by asking your team several important questions:

• Which of our processes/services should be outsourced to AI versus left to human workers? And which tasks can be automated for a competitive advantage?
  
• How can our jobs be reconfigured to optimize human-AI collaboration? And, to ensure we keep tasks where they can be best performed, what human abilities are lacking in AI?
  
• Will our workforce need to be reskilled and reorganized? If so, how can we minimize the impact on staff morale and company culture?
  
• What are our new software/hardware requirements?   
  
• What upfront costs will we need to make to integrate AI? What return on investment (ROI) can we expect? And how quickly can we expect to break even?
  
• How can we best manage AI risks related to data privacy, algorithm bias and model accuracy?
  
• Does our organization have an AI framework and governing body to oversee AI processes and outcomes? If not, what would it take to develop these?
  
• Are there IT vendors we can partner with to accelerate our AI adoption?
  

Answering AI concerns

Carefully answering these questions should allow organizations to apply AI and maximize benefits strategically:

• Focus human efforts on irreplaceable abilities such as creativity, empathy, collaboration, strategy and complex problem-solving. Leverage AI for tasks that require accuracy, endurance, speed and scalability.
  
• Invest in change-management and reskilling to integrate AI and minimize employee anxiety. Promote AI’s role in assisting (rather than replacing) human skills.
  
• Start with a limited proof-of-concept to demonstrate the potential ROI, build capabilities and attract internal support.
  
• Adjust key performance indicators and incentives to encourage staff to adopt AI where appropriate. Continuously monitor your processes for new automation opportunities.
  
• Mitigate risk by partnering with reputable, secure AI vendors.
  

From pyramid to diamond

Many organizations moving to Outsourcing 2.0 with AI will find greater success by also moving to a new organizational structure.

Today, most organizational structures resemble a pyramid. At the pyramid’s base are a large number of frontline workers. They support managers and executives in the hierarchies above them. Information in the pyramid flows up, while decisions and directives flow down. In other words, power and authority are concentrated at the top.

In the near future, however, many organizations that outsource to AI will shift to a structure that resembles a diamond (see Figure 1). As we see repetitive human work undertaken or heavily assisted by AI, workers will reskill to focus on higher-value work and move into more specialized positions. Traditional outsourcing will continue, as organizations leverage the skills of dedicated IT services companies for many critical tasks, allowing them to focus on the core business.

Under the diamond model, power and authority are more evenly distributed. Also, because there’s a greater emphasis on leveraging creativity and innovation for tasks that are unsuitable for outsourcing to AI, some management layers can be optimized, allowing information to flow more easily and decisions to be made more quickly.

Figure 1. The new organizational structure for Outsourcing 2.0 with AI

How DXC can help

Thinking of moving to Outsourcing 2.0, but need help?

DXC has been delivering AI-enabled solutions for more than 20 years. We have extensive knowledge in AI across industries and horizontal business processes. We also have the in-depth skills to help organizations handle their most critical business systems.

DXC’s experienced AI practitioners work with our customers and industry partners to innovate and industrialize AI for enterprise growth. All our work is performed according to a responsible AI framework and best practices. That includes continuous management and refinement as new data becomes available, and as companies seek more sophisticated answers from AI to help realize their business potential.

Learn more about how DXC’s global AI practice can help your organization enjoy the many benefits of Outsourcing 2.0.