Gen AI Will Completely Transform Resource Demand; Are Service Companies Ready?
As generative AI, or Gen AI, evolves and becomes more prevalent in business, service companies face a seismic shift that completely transforms their operations. Gen AI to optimise resources like never before, from freeing creative time to automating technical processes.
Generative AI will add the equivalent of $2.6 trillion to $4.4 trillion annually across the 63 use cases analysed by McKinsey. It will boost productivity and creative problem-solving by 50%, predicts Forrester. But are service companies ready for this new era?
Generative AI (Gen AI) transforms resource demand across various industries. According to a McKinsey Global Survey, one-third of respondents reported that their organisations regularly use Gen AI in at least one business function. The expected business disruption from Gen AI is significant, with respondents predicting meaningful changes to their workforces. They anticipate workforce cuts in certain areas and considerable reskilling efforts to address shifting talent needs.
Regarding service companies’ readiness for this transformation, Tata Consultancy Services (TCS) has strengthened its AI capabilities across its value chain. After training over 150,000 employees in the foundational skills of Generative AI, TCS has launched an AI Experience Zone to foster hands-on proficiency in AI and Gen AI for its employees. It indicates that some service companies are indeed preparing for the AI transformation. TCS has trained about 25% of their workforce on Generative AI as they expect changes in their operations. However, neither TCS, WIPRO, Infosys or HCL Tech have announced the target or chase for Generative AI-driven revenue. The demand for staff remains in a quandary as reports in the media have already taken contrary positions. According to a report by NLB Services, the Indian IT sector will likely witness a positive turnaround, with an 8–10% increase in hiring in 2024. The report suggests that employees engaging in the IT sector will surge by 12–15% in CY 2024, primarily due to the surge in global capabilities centres (GCCs) and the global economy settling down comparatively. However, according to another report by TeamLease Digital, the IT sector will onboard one-third or 32% fewer engineering graduates in fiscal 2024 compared to fiscal 2023. The findings indicate that 1.55 lakh freshers will likely be hired in the IT/technology sector this fiscal compared to 2.3 lakh in the previous year.
Reversing Administrative Creep and Resourcing Bench
In today’s fast-paced business landscape, administrative tasks often creep into our daily routines, taking valuable time that is critical and creative work.
Gen AI can reverse this trend — its ability to automate mundane tasks like content creation, distribution on various communication channels, scheduling appointments with internal and external stakeholders, interacting with customers, and managing paperwork will offer service companies new avenues for greater productivity. With fewer distractions from repetitive administrative tasks, team members can channel their energy toward problem-solving and strategic thinking.
The demand for resources in outsourcing is likely to change significantly with the adoption of Generative AI (Gen AI). Here are some fundamental changes:
- Automation: Gen AI can automate many tasks previously done manually, reducing the need for human resources.
- Efficiency: Gen AI can perform tasks more efficiently and accurately, decreasing resource wastage.
- Shift in Skill Sets: The adoption of Gen AI will cause a shift in the required skill sets. While eliminating some jobs is likely, it will lead to the creation of new jobs, ones that require working with AI and Data skills.
- Cost Reduction: Gen AI can lead to significant cost reductions. For example, marketing functions could shift resources to producing higher-quality content for owned channels, potentially reducing spending on external channels and agencies.
- Transformation of Sales Approach: Gen AI could also change how B2B and B2C companies approach sales.
- Data Management: Enterprises must get the data right for Gen AI to work, but many still need to grapple with legacy technology.
- AI-Enabled Modernisation: Outsourcing partners are beginning to prioritise modernisation and look at how to deal with existing technology issues first to make space for new and exciting things like AI.
- Sustainable Success: Business innovation should be sustainable. Take this example from a leading technology company. The company dominated its market and was quite content with its position. Until it realised it had reached its peak — never ideal in the eyes of stakeholders and investors.
Adopting Gen AI will lead to a shift in the demand for resources in outsourcing. Companies that can integrate Gen AI into their existing infrastructure will be the ones that thrive. While the demand for specific resources may decrease, adopting Gen AI will create new demands. For instance, there will be an increased need for AI specialists and data scientists. Moreover, as companies integrate Gen AI into their operations, they must also invest in training their employees to work with these new technologies. Uncertainty in demand, i.e., managing uncertain demand and visibility to requirements, is a common hurdle in client experiments with Generative AI. The lack of agile and flexible resourcing models for execution is another challenge clients face. Thus, achieving cost-effectiveness and optimising project delivery are crucial client concerns, leading to size reduction. It also impacts the demand for young talent as the resourcing planning follows a time model.
Businesses can optimise their resources by automating repetitive tasks and allocating them towards high-value activities that drive growth and customer satisfaction.
Rising Costs as Current Staff Need Support
As generative AI technology advances, businesses are eagerly embracing its potential. However, with this adoption comes the need for additional support and training for existing staff members. While implementing AI systems can streamline processes and improve efficiency, it also requires time and resources.
Incorporating Gen AI into operations often needs a team of experts who can manage the change while maintaining these complex systems.
It means hiring specialists or training current employees in data analysis and machine learning techniques. Expertise like this isn’t cheap, resulting in higher costs for companies that want to stay ahead of the curve.
Employees will require continuous support from IT professionals who understand how to troubleshoot issues related to generative AI algorithms or software integration. These additional requirements further add to the financial burden on service companies.
Furthermore, regular updates and maintenance of the software used with Gen AI may incur extra expenses. They ensure compatibility between various platforms while optimising performance, which may demand outsourcing or hiring dedicated personnel proficient in enterprise IT management.
Service companies must carefully consider the rising costs associated with supporting their staff through this transformative process to fully capitalise on the benefits offered by generative AI technology while minimising disruptions within existing teams.
Creative and Technical Processes to (Finally) Get Automated
Businesses are looking for opportunities in cyclical ways while dealing with scalability and, on the other hand, to streamline their operations to increase efficacy and efficiency. One area where this is particularly true is in technical processes such as enterprise IT and product development. These processes can often be straight-jacketed, besides being time-consuming and resource-intensive. Still, with the advent of generative AI, which may soon change, the methods can be data-driven and agile.
By harnessing the power of generative AI, companies have the potential to automate many aspects of their technical processes.
Imagine a future where software development is just a few clicks, or complex IT systems are managed effortlessly by intelligent algorithms.
Of course, there will be challenges along the way. Implementing automation technologies requires careful planning and consideration of potential risks. But once implemented successfully, the benefits could be tremendous — reduced costs, faster turnaround times, and improved overall productivity.
Changing Team Dynamics
Traditionally, team structures have been hierarchical, with clear lines of authority and decision-making power. Managers oversee their teams and make critical decisions based on their expertise and experience. However, as gen AI enters the scene, it brings a whole new set of challenges.
Gen AI has advanced capabilities, allowing it to collect data or information, analyse vast data quickly, and recommend or make decisions autonomously.
As a result, team dynamics may shift towards more collaborative approaches rather than top-down leadership styles. Managers may need to become facilitators rather than commanders in a Gen AI world. They must foster an environment where humans work alongside machines as equal partners.
However, the adoption of Gen AI poses challenges not just in the technology itself but in visualising suitable business use cases and ensuring a justified return on investment. Therefore, open communication and joint efforts to build a robust framework will be crucial in navigating the uncharted territory of Gen AI.
While Gen AI is redefining resource demand, the readiness of service companies varies. These companies must assess their AI readiness and take the necessary steps to equip themselves for the AI transformation. It includes technological readiness, strategic planning, execution, innovation, and enabling capabilities.
Additionally, trust between humans and gen AI will be critical for effective team collaboration. Humans must feel confident that machines are reliable sources of information while still maintaining control over final decisions. Building this trust requires open communication channels and transparency regarding the operations of general AI algorithms.
Training Service Staff in Data Operations
Data is the primary agent of change in the age of Gen AI. Companies that can effectively harness and analyse vast amounts of data will have a significant advantage over their competitors. However, this necessitates personnel well-versed in data operations — individuals who can navigate complex datasets and extract meaningful insights.
Training individuals well-versed in data operations on Generative AI (GenAI) can lead to significant effort and cost reduction. Here’s why:
- Efficiency: GenAI can automate many tasks that would otherwise require significant human effort. For example, it can generate code, write reports, and even design graphics.
- Innovation: GenAI can generate new ideas and solutions that humans might not think of. It can lead to innovative approaches to problem-solving.
- Scalability: GenAI model development and training take considerable time, or you can use alternatively existing models available from OpenAi, AWS, or Azure. It can generate more significant outputs than a human could. It can significantly reduce the time and effort required to produce content or analyse large datasets.
- Personalisation: GenAI can generate personalised content for different users or scenarios. It can improve user experience and engagement, leading to better business outcomes.
However, it’s important to note that while GenAI can automate many tasks at scale and find hidden patterns in datasets, it’s not a replacement for human judgment and expertise. Humans still play a crucial role in overseeing the outputs of GenAI, ensuring they meet quality standards, and making strategic decisions based on those outputs.
Generative AI (GenAI) will also have a significant impact on data centre operations:
- GenAI is driving a surge in data centre demand comparable to the cloud.
- The use of GenAI consumption is to increase data centre server infrastructure and operating costs significantly.
- GenAI workloads require high power consumption, with some estimates suggesting that running a GenAI algorithm consumes up to five times more energy than a regular search engine query.
- Data centre environments designed to meet the requirements of GenAI deployments look and behave differently than those designed to house cloud workloads.
- In some respects, the exact nature of these workloads still needs to be discovered.
Data centre operators must understand these impacts and prepare for the increasing demand and changes GenAI brings.
Training service staff in data operations is about more than just teaching them technical skills.
By investing in training programs focused on data operations, service companies can unleash the full potential of their workforce. Employees will gain valuable skills that allow them to take on more advanced roles within the organisation, ultimately leading to improved productivity and efficiency. Moreover, providing opportunities for ongoing learning demonstrates a commitment to employee growth and development.
Will Gen AI Help or Hurt Your Bottom Line?
The answer is a complex one. On the one hand, Gen AI has the power to streamline administrative tasks, free up creative time, automate technical processes, and optimise resource allocation. These benefits can undoubtedly lead to cost savings and increased efficiency for service companies.
Companies can prepare for the adoption of Generative AI (Gen AI) by following these steps:
- Identify a Specific Domain: Identify a specific domain where Gen AI can automate or accelerate tasks, generate ideas, or analyse data.
- Understand the Impact: Consider the specific personas and job functions that will have an impact due to Gen AI and develop a plan for using the technology.
- Prepare Employees: Training employees to use AI systems adequately is critical. There should be a cultural shift towards embracing AI as a supportive tool rather than replacing human capabilities.
- Effective Change Management: Effective change management and upskilling programs are critical to ensure a seamless integration of Gen AI within the organisation.
- Start with People: Companies should dramatically ramp up investing in building talent for developing and using Gen AI.
- Strategic Planning: Business leaders will need to think broadly about how the rollout of Gen AI could affect their organisations daily — especially their people.
- Clear Understanding: Employees and managers should clearly understand Gen AI’s strengths and weaknesses. The linking and usage of the technology to the organisation’s strategic objectives will act as a differentiator.
- Build a Compelling Narrative: As leaders build a compelling narrative using Gen AI, they must identify two or three high-impact applications to explore and bring employees on a value-creating journey.
- Commit to Building Roles, Skills, and Capabilities: Senior leaders must also commit to building the required roles, skills, and capabilities (now and for the future) to continually test and learn with Gen AI and stay ahead of competitors.
- Ethical Deployment: Organisations should ensure the ethical deployment of Gen AI. It includes governance, accountability, and transparency.
Remember, the situation is evolving rapidly, and there is no one correct answer to how — business context matters.
However, there are concerns about rising costs associated with training staff in data operations and supporting current employees using AI technology. Additionally, the changing dynamics within teams may require careful management and adjustment.
All of this will require strategic planning, investment in training programs for your workforce, and a willingness to change and adopt new ways of working.
Service companies that embrace generative AI as a tool for resource optimisation have the potential to get a competitive edge in an increasingly digital landscape. You can email me at Arvind@am-pmassociates.com to learn how to be a leader and not a laggard.
