Yet, the industry stands at a crossroads. About 25% of biopharma firms and 10% of medtech players already report tangible business value from AI, including cost reductions and revenue increases of at least 5%. These early adopters are also seeing measurable improvements in speed, compliance, and agility. In contrast, nearly 60% of manufacturers remain cautious, with no clear GenAI strategy or at best, a wait-and-see stance. This divide underscores an urgent reality: health care organizations that hesitate risk falling behind in efficiency, quality, and competitiveness.

Why Health Care Operations Are Ripe for GenAI

Health care operations — spanning procurement, supply chain, manufacturing, quality, regulatory compliance, and workforce training — are complex, resource-heavy, and prone to inefficiencies.

Traditional automation and analytics have delivered incremental gains, but GenAI goes further by:

• Understanding context and generating insights beyond structured data.
• Automating knowledge-intensive tasks like deviation analysis, regulatory reporting, and training.
• Creating new workflows that were previously unimaginable, such as end-to-end automated tech transfers.

This leap means health care leaders can shift from doing digital to being digital: embedding intelligence into the DNA of their operations.

The Three Value Plays: Deploy, Reshape, Invent

BCG identifies three complementary ways GenAI can be applied in health care operations:

1. Deploy – Boost Productivity with Off-the-Shelf Tools

This is the fastest path to value. Off-the-shelf GenAI solutions can be integrated into existing workflows to streamline repetitive tasks:

• Shop-Floor Agents: Provide real-time troubleshooting based on SOPs, reducing downtime and boosting throughput.
• Logistics Execution: Automate documentation and scheduling to accelerate supply chains.
• Procurement Analytics: Optimize spending by analyzing supplier contracts and historical data.

2. Reshape – Reinvent Critical Workflows End-to-End

Here, GenAI is used to reengineer complex processes, delivering exponential improvements:

• Quality & Regulatory Affairs: Automating deviation investigations, generating root-cause analyses, and harmonizing compliance reporting.
• Risk Management: Using GenAI to flag anomalies across assets and processes before they escalate.
• Regulatory Submissions: Drafting technical documents and stability reports at scale, reducing cycle times.

Case in point: GenAI-assisted deviation handling (Exhibit 2) can clarify trends, classify issues by severity, and propose corrective actions, cutting investigation timelines from weeks to days.

3. Invent – Create New Business Models and Experiences

The most transformative play is using GenAI to invent entirely new operating models:

• Tech Transfer Reinvention: AI agents can automate planning, predict risks, and recommend optimal process shifts across sites. This minimizes variability and accelerates transfers from months to weeks.
• AI-Powered Learning Ecosystems: Personalized assistants can curate training, track learning progress, and assess readiness for regulatory audits.
• Embedded Insurance Models (for medtech): Using GenAI to create bundled offerings, e.g., device + predictive maintenance + risk coverage.

The most successful organizations will not choose between these plays — they will run all three simultaneously, balancing short-term wins with long-term transformation.

High-Impact Applications Across Operations

GenAI’s versatility means it touches nearly every link in the health care value chain:

• Procurement: AI models optimize supplier contracts, ensuring cost-effective spending.
• Supply Chain: Demand forecasting improves accuracy, while GenAI agents automate logistics execution and track anomalies.
• Manufacturing: Shop-floor AI agents monitor KPIs, flag process deviations, and optimize yield.
• Quality & Regulatory: GenAI accelerates deviation investigations, creates technical documents, and ensures continuous compliance.
• Learning: AI-driven training assistants personalize workforce upskilling, bridging capability gaps faster.

By 2025, health care manufacturers deploying GenAI across these domains may realize more operational value in a single year than in the previous three combined.

The Deviation-Management Breakthrough

Deviation management — historically a time-consuming, manual process — is a standout use case for GenAI. Today, resolving deviations involves multiple steps: logging the event, classifying its scope, conducting root-cause analysis (RCA), planning corrective and preventive actions (CAPA), and closing with QA approval. Each step consumes hours of skilled labor.

GenAI can transform this process:

• Event Reporting: Auto-transcription tools improve accuracy in logging.
• Classification: Assisted classification avoids unnecessary escalations.
• RCA: Automated searches highlight similar historical deviations, generating root-cause summaries.
• Remediation: AI suggests corrective actions based on past effectiveness.
• QA & Closure: Automates text reviews and retrieves regulatory assessments.
• Monitoring: Detects trends across assets and process steps to preempt future issues.

This shift creates two key advantages:

1. Efficiency — time saved in deviation handling, leading to faster product release.
2. Effectiveness — improved compliance, reduced cycle times, and higher confidence in audit readiness.

Six Enablers for Scaling GenAI

Many pilots fail because organizations underestimate what it takes to scale GenAI. Six enablers separate leaders from laggards:

1. Set a Bold Ambition
2. Prioritize Value-Based Use Cases
3. Strengthen Data Foundations
4. Leverage Platforms & Partnerships
5. Align People, Processes, and Change
6. Establish Responsible AI Policies

What This Means for CXOs

For senior leaders, the message is clear: GenAI is no longer experimental — it is existential.

• Revenue Growth: GenAI can boost top-line performance by improving time-to-market and creating new offerings.
• Cost Efficiency: Automating regulatory and operational tasks reduces overheads and rework.
• Agility: Faster deviation handling and predictive risk management make organizations more resilient.
• Talent Transformation: GenAI enables employees to focus on higher-value work, while AI-driven learning bridges skills gaps.

Leaders must shift their perspective from “Should we use GenAI?” to “Where can GenAI create the most impact, and how fast can we scale it?”

The Road Ahead

Health care organizations that act decisively today will set the benchmarks for speed, compliance, and patient outcomes tomorrow. With competitors already embedding GenAI into their operations, the cost of inaction is not neutrality — it is obsolescence.

The winning formula is simple yet demanding:

• Deploy GenAI for immediate productivity gains.
• Reshape complex workflows to drive exponential efficiencies.
• Invent new experiences and models that redefine patient care and operational excellence.

For CXOs, the path forward is less about technology alone and more about strategic courage, cultural alignment, and disciplined execution. GenAI in health care is not a future story — it is unfolding now. The question is: will you lead the transformation, or watch others define it?

The post Generative AI: The Next Frontier for Health Care Operations appeared first on Quantility.

For decades, Global Capability Centers (GCCs) in India have been synonymous with cost arbitrage and operational efficiency. Initially established as offshore support hubs, these centers primarily focused on back-office functions, IT services, and shared operations for multinational corporations. However, as global businesses face increasing market volatility, technological disruptions, and rising customer expectations, GCCs are undergoing a fundamental transformation.

Today, India hosts over 1,500 GCCs, employing more than 1.5 million skilled professionals and contributing $46 billion annually to the economy. Yet, the most significant shift is how GCCs are evolving from cost-saving units to strategic business enablers. The next decade will determine whether India’s GCCs remain competitive or become obsolete.

This article explores how AI, digital transformation, sales enablement, and strategic Go-To-Market (GTM) execution are redefining India’s GCC landscape, making them indispensable to global enterprises.

1. The Evolution: From Cost Centers to Business Enablers

The old model: Efficiency and Process Optimization

Historically, multinational corporations set up GCCs in India to leverage:

• Labor cost efficiency: India’s vast talent pool at lower operational costs.
• Process standardization: Streamlining workflows across global locations.
• IT and operational support: Handling backend operations, infrastructure maintenance, and compliance functions.

While these benefits drove GCC expansion, they also created a perception that GCCs were merely support functions, rather than value drivers.

The new model: Driving Innovation and Growth

Today, the most successful GCCs are shifting their focus from cost efficiency to business impact, enabling global enterprises to:

• AI-Powered Decision Making – Developing advanced analytics and AI-driven business models.
• Customer Experience (CX) Innovation– Creating hyper-personalized engagement strategies.
• Revenue Generation – Leading sales enablement and GTM executionfor global markets.
• Banking & Financial Services (BFSI) Leadership – Powering AI-driven fraud detection, risk modeling, and compliance automation.

Case Study: How a GCC Transformed from Support to Strategy

A leading American bank with a GCC in Bangalore transitioned from traditional process management to an AI-driven transformation hub. By implementing AI-powered risk modeling, the center:

• Reduced financial fraud incidents by 30%.
• Accelerated compliance reporting time by 50%.
• Developed AI-driven credit scoring models used globally.

The result? The bank’s GCC became a core strategic asset rather than an operational necessity.

2. AI and Automation: The Game Changers for GCCs

The integration of Artificial Intelligence (AI) and automation is enabling GCCs to take on higher-value roles in innovation, decision-making, and revenue generation.

AI-Driven GCC Functions in Banking & Financial Services

• Risk & Compliance: AI models for fraud detection and compliance automation.
• Customer Insights & CX: AI-powered chatbots, sentiment analysis, and predictive personalization.
• AI in Credit Scoring: Real-time AI-based risk assessments reducing loan approval times from weeks to hours.

Example: AI-Powered Fraud Detection

HSBC’s India GCC implemented an AI-driven compliance monitoring system, reducing financial crime risk by 40% and enhancing regulatory reporting efficiency.

💡 Key Insight: AI is transforming India’s BFSI-focused GCCs into centers of predictive analytics and data-driven decision-making.

3. Sales Enablement & Revenue Growth: A New Frontier for GCCs

GCCs are no longer just cost centers; they are becoming direct revenue contributors by powering sales enablement and go-to-market execution.

How AI is Enhancing Sales Enablement

Predictive Lead Scoring – AI prioritizes high-value leads based on intent and engagement.

AI-Powered Account-Based Marketing– Hyper-personalization for B2B sales.

Dynamic Pricing & Revenue Optimization – AI-driven competitive pricing models for maximum conversions.

Case Study: AI-Powered GTM Execution for a Leading FinTech Firm

A UK-based FinTech company leveraged its India GCC for AI-driven market segmentation and expansion strategy. The result: ✔ 25% higher conversion rates using predictive analytics. ✔ 30% increase in sales efficiency through AI-driven sales outreach. ✔ Expansion into 3 new global markets within 12 months.

The Takeaway: GCCs are now actively driving market expansion and revenue growth, making them integral to global GTM strategies.

4. The Future of India’s GCCs: A $100B Opportunity

With the rapid adoption of AI, India’s GCC market is projected to surpass $100 billion by 2030. But success will depend on:

Key Growth Drivers

AI, Data & Cloud-Led Innovation: Investment in AI-powered solutions.

Strategic Global Alignment: GCCs as strategic enablers, not just support hubs.

Upskilling & Talent Transformation: Moving from BPO to high-value AI-driven capabilities.

What GCC Leaders Must Prioritize

P&L Ownership– Moving beyond cost savings to measurable business impact.

End-to-End AI Implementation– Creating AI-driven decision frameworks.

Cross-Functional Integration – GCCs as hubs for AI, consulting, and revenue enablement.

Final Thought: Are GCCs Ready for the Next Era?

The question is no longer whether GCCs will survive but how they will evolve. Companies that fail to transition from cost centers to strategic growth engines will struggle to remain competitive in a rapidly changing business landscape.

Are India’s GCCs ready to lead the AI-driven future?

Let’s discuss! How do you see GCCs shaping global business strategy? Drop your thoughts below!

The post India’s GCC Evolution: The Shift from Cost Hubs to Strategic Growth Engines appeared first on Quantility.

In this article, we’ll explore how businesses can leverage reskilling and upskilling strategies in the AI age, backed by data from leading firms such as PwC, Deloitte and McKinsey & Company .We will also examine compelling case studies and best practices from companies leading the charge in workforce transformation.

According to McKinsey & Company, nearly 60% of all occupations have at least 30% of their activities that are automatable with current technologies. Moreover, they estimate that by 2030, 375 million workers globally will need to switch occupational categories due to automation and AI. This seismic shift means that the way businesses think about talent must evolve from simply filling roles to developing skills and capabilities that align with future job requirements.

PwC’s Global CEO Survey supports these findings, with 79% of CEOs citing a shortage of key skills as one of their top three threats to growth. The skills gap, exacerbated by the rapid adoption of AI, underscores the need for businesses to invest in training programs that enable their workforce to move into strategic roles that machines cannot replicate.

The Reskilling Revolution: Why It’s Not Just About New Skills

Reskilling isn’t just about acquiring new technical skills. While knowledge of AI, machine learning, and data science is important, it’s equally crucial for employees to develop skills that machines cannot easily perform—such as emotional intelligence, leadership, and adaptability.

World Economic Forum’s Future of Jobs Report highlights that by 2025, 85 million jobs may be displaced by automation, but 97 million new roles will emerge that require a combination of technical and soft skills. These roles will increasingly rely on human judgment, creativity, and problem-solving—capabilities that AI, despite its advancements, cannot match.

The reskilling revolution demands a holistic approach to workforce transformation. Companies need to focus not only on the technical competencies required to work alongside AI but also on cultivating the emotional and cognitive skills that will drive strategic decision-making and innovation.

Upskilling for Strategic Roles: Where Should Organizations Start?

For #CHROs and senior leaders, the question is not if but how to upskill their workforce for strategic roles. Here are several critical areas of focus:

• Identify Future Skill Requirements Begin by analyzing which skills will be most valuable in the future. According to Deloitte’s Human Capital Trends, roles that involve critical thinking, creativity, and emotional intelligence will see increased demand, while routine, manual, and administrative tasks will be automated.
• Prioritize Soft Skills While digital skills are a necessity, soft skills such as adaptability, problem-solving, and collaboration are becoming equally important. A report by LinkedIn Learning shows that 57% of senior leaders say that soft skills are more important than hard skills for future leadership positions.
• Create Tailored Learning Pathways One-size-fits-all training programs won’t cut it. Employees at different stages of their careers and across various functions will have unique learning needs. Designing tailored learning pathways, with options for self-paced, on-the-job, and collaborative learning, ensures employees can develop the skills most relevant to their roles.
• Leverage AI in Learning Ironically, AI can be part of the solution. AI-powered learning platforms can help tailor training programs to individual learning styles, provide real-time feedback, and recommend additional resources. Companies like AT&T have used AI to create personalized upskilling paths for employees, which has helped them stay competitive in the telecom industry.

AT&T Business Billion-Dollar Workforce Transformation

One of the most well-known examples of a successful reskilling initiative is AT&T’s Future Ready program. Faced with the challenge of digital transformation, AT&T made a bold decision in 2013 to invest $1 billion into reskilling its workforce. AT&T’s CEO recognized that over half of its 250,000 employees were working in jobs that would become obsolete due to advances in technology.

To address this, AT&T launched a comprehensive workforce transformation initiative, focusing on reskilling employees for high-demand roles like cloud computing, data analytics, and cybersecurity. The company partnered with online education platforms such as Coursera and Udacity to provide employees with access to courses tailored to future business needs.

By 2020, more than 100,000 AT&T employees had completed retraining programs, allowing the company to fill crucial roles internally and reduce its reliance on external hiring. This reskilling initiative not only saved jobs but also helped AT&T remain competitive in an industry undergoing rapid technological change.

Why Upskilling is a Business Imperative, Not a Luxury

For many organizations, upskilling has moved from a “nice-to-have” to a business imperative. The economic and competitive pressures of the AI age mean that companies can no longer rely solely on hiring external talent to fill skills gaps. Instead, they must look inward, investing in their current workforce to build the capabilities they need for the future.

Research by PwC found that 74% of employees are ready to learn new skills or retrain to remain employable. Moreover, companies that invest in upskilling see tangible returns: a study by Boston Consulting Group found that organizations with well-established upskilling programs saw productivity improvements of up to 30% and a 20% increase in employee satisfaction.

Role of CHROs in Leading the Upskilling Agenda

CHROs are at the forefront of this transformation. As workforce architects, they are tasked with ensuring that employees have the skills, knowledge, and tools to succeed in an increasingly automated world. Leading firms like Unilever, Siemens and IBM have empowered their HR leaders to spearhead reskilling initiatives, integrating them into broader corporate strategies.

At Unilever, for example, the company launched its Future Fit program, aimed at helping employees build digital skills while also focusing on lifelong learning. The program, led by the CHRO, emphasizes both digital literacy and personal development, ensuring employees are equipped to navigate future challenges.

How to Measure the Success of Reskilling and Upskilling Programs

It’s essential to evaluate the effectiveness of reskilling and upskilling programs. Here are some key metrics to consider:

1. Skill Acquisition: Track the number of employees who complete upskilling programs and attain certifications in new skills relevant to their roles.
2. Internal Mobility: Measure the rate of internal promotions or lateral movements into new, more strategic roles after employees complete training.
3. Employee Engagement: Surveys or pulse checks can assess whether employees feel supported in their development and if they find the programs beneficial.
4. Business Impact: Ultimately, the success of reskilling initiatives can be measured by their impact on business outcomes, such as increased productivity, revenue growth, or reduced turnover rates.

Siemens Approach to Workforce Transformation

Siemens a global leader in industrial manufacturing, has been at the forefront of using AI and automation to enhance operations. Recognizing that its workforce needed to evolve alongside technology, Siemens launched its Future Skills Initiative. This initiative aimed to reskill 300,000 employees globally, focusing on data analytics, digital twin technology, and automation.

Siemens’ approach centered on digital learning ecosystems where employees could access customized learning content, collaborate with peers, and gain hands-on experience with emerging technologies. By providing a flexible, self-directed learning environment, Siemens empowered employees to take control of their career development while meeting the company’s strategic goals.

As a result, Siemens has seen a 20% increase in internal mobility, allowing the company to fill key roles with existing employees and reduce its reliance on external recruitment. Siemens’ reskilling efforts have been instrumental in its transformation into a digital-first industrial powerhouse.

Conclusion: Staying Ahead in the AI Age

The rise of AI and automation presents both challenges and opportunities for businesses. Organizations that fail to invest in reskilling and upskilling their workforce risk falling behind, as the demand for strategic, high-skill roles continues to grow. On the other hand, companies that embrace workforce transformation will position themselves as leaders in their industries, capable of adapting to the rapid pace of technological change.

CHROs have a critical role to play in leading this revolution. By identifying future skill requirements, prioritizing soft skills alongside technical competencies, and creating tailored learning pathways, they can ensure their workforce is prepared for the future.

As demonstrated by companies like AT&T and Siemens, reskilling and upskilling are not just strategies for managing the present but essential investments in building a future-ready workforce that can thrive in the age of AI.

References:

• McKinsey & Company , “Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation”
• PwC Global CEO Survey
• World Economic Forum “Future of Jobs Report”
• Deloitte “Human Capital Trends”
• Boston Consulting Group (BCG) “The Upskilling Imperative”

The post Reskilling and Upskilling in the AI Age appeared first on Quantility.

Research by CUNA Mutual Group suggests that only 25% of credit unions are seeing consistent membership growth. Many factors, such as the digital-first expectations of younger generations and increasing regulatory requirements, make it harder for credit unions to keep pace. The message is clear: credit unions must evolve or risk stagnation.

A Dual Strategy for Growth: Technology Partnerships and Workforce Reskilling

To address these growth challenges, credit unions must rethink their approach by embracing technology partnerships and investing in workforce reskilling. This combined strategy enables them to enhance member experiences, improve operational efficiency, and build a future-ready workforce.

1. Leveraging Technology Partnerships for Enhanced Member Experiences

Technology is now a critical component of member engagement in financial services. Members expect seamless, fast, and personalized digital experiences. For credit unions, collaborating with technology providers is an efficient way to modernize without the heavy burden of building in-house capabilities from scratch.

• Digital Transformation Through Fintech Partnerships: According to Deloitte Consulting, 64% of financial institutions are exploring fintech partnerships to enhance their digital offerings. By partnering with fintechs, credit unions can introduce innovative digital services—like mobile banking, AI-driven customer support, and tailored financial advice—catering to the digital needs of today’s members. Companies like Tyfone, for instance, provide secure digital banking solutions tailored for credit unions, making it easier for members to access financial services anytime, anywhere.
• Data-Driven Personalization: Data analytics enables credit unions to offer personalized experiences by understanding member behavior and preferences. McKinsey reports that personalization can drive a 15-20% increase in customer satisfaction and retention. By utilizing data-driven insights, credit unions can proactively address member needs, which strengthens loyalty and promotes long-term relationships.
• Scalability and Agility with Cloud Technology: According to a PwC report, 70% of financial institutions consider cloud technology essential for scalability and innovation. By adopting cloud-based platforms through partnerships, credit unions can roll out new digital services quickly and cost-effectively, keeping up with evolving member expectations without heavy capital investment.

2. Reskilling the Workforce for a Digitally-Enabled Future

While technology partnerships provide the digital infrastructure, a skilled and adaptable workforce is essential to fully leverage these tools and ensure member satisfaction. Reskilling the workforce not only equips employees with relevant digital skills but also enhances their ability to interact meaningfully with members.

• Upskilling for Digital Proficiency: A LinkedIn report states that 57% of financial services employees need reskilling to work effectively with digital tools. Providing training on customer relationship management (CRM) systems, cybersecurity protocols, and data privacy practices can empower employees to better serve members in a secure digital environment.
• Building Soft Skills for Enhanced Member Engagement: With the rise of digital services, soft skills—such as communication, empathy, and emotional intelligence—are becoming more crucial. According to a study by IBM, 90% of executives cite soft skills as essential for workforce success. Credit unions can build programs to enhance these skills, ensuring employees can provide personalized, human-centric service even in a digital-first context.
• Fostering a Culture of Continuous Learning: A PwC survey reveals that 74% of CEOs are concerned about the availability of digital skills within their organizations. Credit unions can address this concern by promoting a culture of continuous learning, offering employees access to resources, workshops, and certifications. This mindset encourages employees to keep up with industry developments, regulatory changes, and evolving member needs.

The Benefits of an Integrated Approach to Growth

By combining technology partnerships with workforce reskilling, credit unions can realize several key benefits:

1. Improved Member Retention and Loyalty: A Salesforce survey found that 84% of customers prioritize experiences as much as products. Digital services that are easy to use and customized to member needs foster deeper loyalty and improve retention. Experiential learning initiatives also build staff confidence, enabling them to provide exceptional service.
2. Attracting New, Younger Members: The Millennial and Gen Z demographics favor institutions that offer innovative tech solutions. According to a study by BAI Research, 87% of younger consumers say that digital access is essential in choosing a financial institution. By enhancing digital capabilities, credit unions can attract and retain these tech-savvy members.
3. Operational Efficiency and Cost Savings: McKinsey & Company reports that automating and optimizing operations can reduce costs by up to 30%. By leveraging cloud technology, data analytics, and automation, credit unions can streamline operations, reduce human error, and focus resources on member engagement rather than administrative tasks.
4. Enhanced Employee Satisfaction and Retention: A study by Gallup shows that employees who feel empowered and supported in learning new skills are 2.5 times more likely to stay with their organization. By providing reskilling opportunities, credit unions create a motivated, engaged workforce invested in the credit union’s mission and success.

As the financial services landscape continues to evolve, U.S. credit unions face unique challenges in achieving sustainable growth. A strategy that combines technology partnerships with workforce reskilling offers a pathway forward. Through these partnerships, credit unions can introduce cutting-edge digital experiences that meet the demands of modern members. Meanwhile, reskilling efforts ensure that employees are equipped to deliver high-quality service and adapt to ongoing changes.

We are committed to supporting credit unions on their growth journey. We provide the tools and expertise needed to implement effective technology solutions and empower employees through targeted reskilling. Together, we can help credit unions overcome growth challenges and build a resilient, member-focused future.

The post The Growth Conundrum Facing Credit Unions appeared first on Quantility.