Rajesh Nambiar, chairman of Nasscom and managing director of Cognizant’s India unit, expressed concerns regarding the workforce in process-oriented industries, traditionally known as BPO. He noted the imminent threat posed by AI engines that could quickly replace human roles. This sentiment highlights the urgency of the changes taking place in the enterprise software and IT service sectors.
For over two decades, global organisations have adhered to a proven methodology for procuring enterprise software and implementing IT services.
This methodology typically involves choosing large-scale software or SaaS vendors such as SAP, Oracle, Salesforce, and Workday to fulfil various business requirements, followed by the selection of IT service providers like Infosys, TCS, Accenture, or Wipro for deployment, customisation, and ongoing support. Business Process Outsourcing (BPO) providers would manage these systems to perform specific tasks, including customer service, accounts receivable/payable, and procurement.
This framework delivered substantial value, enabling companies to manage, automate, and enhance their processes while generating considerable employment opportunities and returns for stakeholders within both software and IT/BPO service sectors. Nevertheless, the rise of generative AI (GenAI) and agentic models is upending this standard approach, heralding what may be termed “The Great Reset” of the enterprise technology landscape.
This “Great Reset” expands upon the trends outlined in StartupSuperb’s report on AI-powered Vertical SaaS, which discusses how AI-driven, industry-centric solutions are surpassing generic SaaS by providing customised outcomes. Currently, we examine how this disruption impacts the extensive field of enterprise technology, encompassing both IT and BPO services.
This article explores how agentic systems utilising GenAI and autonomous “AI employees” are fundamentally transforming workflows, value chains, and the entire framework of enterprise service delivery.
A System Under Strain: The Traditional Enterprise Model
Since the early 2000s, the integrated ecosystem of SaaS providers and IT/BPO service companies has altered how enterprises function:
- Cost Efficiency: The availability of standardised software and off-the-shelf solutions allowed businesses to avoid the expensive and time-consuming process of developing custom software from scratch.
- Scalability: SaaS vendors offer wide-ranging, adaptable solutions suitable for large-scale organisations, while IT/BPO services facilitate the scaling, customisation, and global support of these solutions.
- Operational Efficiency: BPO companies operate standardised software for business processes on a large scale, enhancing workflows across functions such as customer service, procurement, and HR.
This structure fostered a mutually beneficial environment, allowing SaaS companies, IT/BPO service providers, and global enterprises to prosper through a continuous loop of software procurement, implementation, and support.
AI-Driven Disruption: A New Paradigm For Customisation And Automation
The rapid advancements in AI technology, particularly GenAI, have lowered the barrier to creating custom solutions. Organisations can now harness AI-native tools to design bespoke software in significantly less time and at a reduced cost.
GenAI, in conjunction with agentic models—AI-driven agents capable of executing tasks autonomously—grants enterprises the ability to automate workflows without depending on traditional SaaS vendors or IT/BPO services for expertise and implementation.
Key elements influencing this transformation include:
- Dramatic Productivity Boosts in Software Development: GenAI models and AI-assisted coding tools expedite software development, enabling organisations to create custom applications tailored to their unique requirements.
- AI Employees in Action: Agentic models, often described as “AI employees,” can independently manage a range of tasks, eliminating the necessity for traditional human-operated BPO services for specific functions, resulting in significant cost savings and improved efficiency.
- Reduced Time and Cost of Custom Software: Presently, the process of developing custom AI-powered software is not only expedited but also considerably cost-effective, allowing organisations to replace standard SaaS solutions with more targeted, efficient AI-native software. An example of this trend is Klarna’s transition from Salesforce and Workday to their own AI-native system.
The Shifting Landscape: SaaS Giants And IT/BPO Struggling To Adapt
As discussed in a prior article regarding AI-powered Vertical SaaS, industries are transitioning away from generic solutions in favour of bespoke, AI-driven strategies that yield clear results. However, this shift extends beyond vertical SaaS; it indicates a broader transformation impacting both enterprise software and IT/BPO sectors.
To maintain competitiveness, traditional SaaS vendors like Salesforce are evolving towards AI-based solutions. A case in point is Salesforce’s Agenforce, which showcases a growing emphasis on AI-driven automation.
Similarly,
Highlights
Challenges Faced by IT and BPO Services Providers
IT and BPO service providers are encountering stagnant growth and noticeable declines in profit margins due to the emergence of AI-native startups and agencies, which utilise highly efficient AI-savvy talent. Despite striving to keep up with the advancing AI landscape, traditional providers are grappling with various structural obstacles:
- Prolonged Implementation Cycles: Traditional software dependencies and customisation processes hinder large enterprises from swiftly adopting AI-enhanced solutions.
- Outdated Workforce and Skill Gaps: Although IT and BPO firms are in a race to upskill their employees, AI-centric workers in startups demonstrate superior productivity and innovation, making it difficult for established providers to compete in quality and efficiency.
- Profit Margin Pressures: New AI solutions are addressing business needs directly without the need for intermediaries, leading to reduced profit margins for IT and BPO services and disrupting a model that has traditionally generated double-digit growth.
The Great Reset: A New Era of Tech Dominance
In the next 2–3 years, a considerable upheaval in the technology sector is anticipated. The disruption brought by AI could herald what may be termed “The Great Reset,” where success is reserved for those who completely adapt to AI-native methods in software and service delivery.
Companies such as Klarna are already showcasing this transition in action. Within its initial month, Klarna’s AI assistant managed 2.3 million customer service interactions across 35 languages, equivalent to the work performed by 700 full-time agents. By flawlessly integrating AI to automate customer engagements, Klarna has effectively decreased costs and improved customer satisfaction, highlighting the competitive edge for companies that embrace AI-driven innovation in their core functions.
Who Will Rise to the Top?
- AI-Native Vertical SaaS and Solution Providers: These organisations are poised to redefine future enterprise technology through complex systems that enable profound customisation and configuration without being hindered by legacy platforms or cumbersome implementation strategies.
- New-Age Agencies and Startups: Emerging startups and agile agencies that focus on delivering bespoke, AI-driven solutions are well-positioned to challenge traditional IT and BPO providers. By leveraging streamlined AI-native teams that emphasise innovation, efficiency, and speed, these newcomers can provide affordable, highly tailored alternatives. Their capacity to quickly adapt to client requirements, incorporate advanced AI technologies, and circumvent the inefficiencies of outdated processes makes them appealing partners for companies seeking to modernise and optimise their operations. This shift represents a substantial market share opportunity, signalling a transformative period for the IT services sector.
- Enterprises Adopting Agentic Workflows: Companies that lead the development of in-house agentic AI models are set to redefine the core of enterprise workflows. These intelligent agents automate intricate, end-to-end processes, challenging the conventional dependence on fragmented SaaS solutions and labour-intensive BPO services. As these systems streamline operations with minimal human input, businesses will gradually transition from employing multiple standalone applications to adopting unified, AI-driven ecosystems. This fundamental change not only boosts efficiency and scalability but also simplifies operations, making traditional methodologies increasingly irrelevant. The growth of agentic AI signifies a dramatic advancement in enterprise technology, fundamentally altering how organisations pursue productivity and process optimisation.
Preparing for the Future – Thriving in an AI-Driven World
To secure leadership in this evolving technological landscape, legacy SaaS and IT/BPO providers must implement significant changes in their AI strategies. Businesses aspiring for success should consider several critical approaches:
- Exhibit Domain Expertise: Companies with profound industry knowledge possess a competitive advantage in comprehending their clients’ specific needs. An astute understanding of sector-specific workflows, regulations, and operational hurdles enables the development of AI solutions that deliver real value and align with practical requirements.
- Achieve Seamless Integration with Existing Systems: Success within the AI realm hinges on not only crafting new technologies but also ensuring their compatibility with current systems. Companies that excel at merging AI with existing applications, databases, and workflows—providing a smooth user experience across platforms—will differentiate themselves from competitors who neglect this vital aspect.
- Combine GenAI with Established Data and Tools: The true potential of GenAI emerges from merging it with organisational data and existing tools to uncover insights, streamline processes, and provide predictive capabilities that feel integrated within the business’s current technology environment. Organisations effective in linking the new capabilities of GenAI with established data and APIs will realise significant efficiencies and grow indispensable to their clients.
- Develop an AI-Ready Workforce: The task of retraining a substantial workforce to align with the demands of AI and GenAI presents a considerable challenge. Legacy providers are working to upskill employees in AI-driven development, automation, and data analysis. Given the magnitude of this transition, achieving a fully skilled workforce in AI will be neither immediate nor simple, especially amidst rapidly evolving AI technologies. TCS has reportedly engaged in over 200 projects in GenAI with clients, likely integrating GenAI with existing client data and systems.
- Strategic Acquisitions for Skill and Technology Enhancement: Due to the complexities of reskilling an entire organisation, many IT/BPO firms are actively pursuing acquisitions to bring AI talent, domain expertise, and innovative technologies into their operations. This trend is expected to gain momentum as legacy companies seek partnerships with AI-native startups and agencies to accelerate their transformation and swiftly bring AI-enhanced solutions to market.
The urgency for legacy SaaS and IT/BPO providers to adopt an AI-centric approach is at an all-time high. While traditional models have served a substantial purpose over the past two decades, businesses are now primed for an avant-garde methodology that maximises efficiency, automation, and customisation.
As we approach the anticipated great reset, it is evident that the traditional playbook is nearing its conclusion. The speed of AI advancement will compel organisations to rethink procurement strategies, workforce management, and technology integration. In this dynamic environment, only those that adapt promptly will remain relevant, heralding a new age characterised by the transformative power of AI across all facets of enterprise software and service delivery.
By focusing on domain expertise, ensuring seamless integration, and effectively adapting to GenAI, alongside reinforcing their AI readiness through strategic acquisitions, established players can significantly enhance their chances of thriving amid the post-AI disruption landscape. Nevertheless, the transition will be formidable, and those who falter may find themselves overshadowed by nimble competitors and AI-native startups. In the forthcoming years, an intensifying race for relevance in an AI-enhanced world is expected, which is likely to incite a seismic shift in the global enterprise technology landscape.