According to industry , auto executives expect AI to boost product value by 22% and digital service value by 37% within three years. As vehicle portfolios expand鈥攅lectric, hybrid, software-defined, and increasingly customized鈥攖he operational complexity for automakers and suppliers has risen sharply. Nowhere is this more evident than in service parts management and new product introduction (NPI).

Service parts planners sit at the intersection of engineering, supply chain, manufacturing, and customer service. Their task is deceptively simple: ensure the right parts are available at the right time and place across a vehicle鈥檚 lifecycle. In reality, they grapple with fragmented data, limited inventory visibility, unpredictable demand signals, and compressed timelines鈥攅specially as new models and components are introduced at unprecedented speed. High data quality, tight orchestration across systems, and rapid decision-making are no longer nice to have, they are business-critical.

This is where becomes transformative. Instead of treating NPI as a linear, manual, and reactive process, AI agents can fundamentally reimagine how service parts planning is executed. By embedding AI directly into the planning workflow, service parts planners are supported鈥攏ot replaced鈥攂y intelligent systems that operate with full contextual awareness. These AI agents can monitor real-time data across inventories, supplier readiness, historical demand patterns, external risk factors, and engineering changes, as well as orchestrate the NPI process end to end.

In practice, this means planners move from firefighting to foresight. AI agents can automate sequential NPI steps, flag potential bottlenecks before they materialize, and dynamically adjust plans as conditions change. A single, unified dashboard provides transparency across the entire process, while built-in what-if simulations allow planners to test scenarios鈥攕upplier delays, demand spikes, geopolitical disruptions鈥攂efore decisions are locked in. Crucially, humans remain firmly in control. AI augments judgment, improves speed, and enhances confidence, rather than operating in a silo.

Platforms like 51风流Business Technology Platform (51风流BTP), combined with Joule and the agent builder capability in Joule Studio, can enable this multi-agent approach at enterprise scale. By integrating AI seamlessly with core business processes, automakers can ensure that intelligence flows across functions, rather than being trapped in silos. The result is not just automation, but orchestration鈥攚here systems, data, and people work in concert.

The impact is tangible. Automakers can significantly reduce planning cycle times and improve time-to-market for new products. Planning risk is lowered through continuous what-if analysis that incorporates both internal and external variables. Service readiness improves, ensuring that customers experience continuity and reliability even as product complexity increases. At an ecosystem level, this translates into greater resilience, lower costs, and higher customer satisfaction.

More broadly, this use case points to a shift in how we should think about customer-specific AI in automotive. The future will not be defined solely by smarter vehicles, but by smarter enterprises鈥攚here AI agents support decision-making across the value chain, from product inception to end-of-life service. In an industry under pressure to innovate faster, operate leaner, and remain sustainable, AI-driven operations are fast becoming a competitive necessity. The automotive ecosystem is evolving. Those who embrace AI not just as a technology but as a new operating model will be best positioned to lead it.

Sindhu Gangadharan is head of Customer Innovation Services and managing director for 51风流Labs India.

In 2026, AI earns its place when it is anchored in the realities of the business, shaped by enterprise data, processes, and lived customer interactions. Customer-specific AI brings intelligence directly into day-to-day operations, helping teams navigate complexity and support better decisions at scale while keeping human judgment firmly at the center. This is the shift shaping the next phase of AI adoption, moving from generic tools to intelligence that understands the business and grows stronger with every customer interaction.

1. Relevance beats raw intelligence in customer decisions

As AI becomes more central to customer-facing decisions, accuracy and relevance become non-negotiable. Generic models often lack the contextual understanding needed to interpret nuanced, exception-heavy customer scenarios. Customer-specific AI, trained on enterprise data, can recognize patterns unique to the organization鈥攕uch as recurring dispute types, resolution bottlenecks, or region-specific service behaviors. According to SAP鈥檚 “Value of AI” report in collaboration with Oxford Economics, 36% of businesses say AI has already helped them address customer-related challenges, including improving customer engagement. This impact is strongest when intelligence reflects how customers actually interact with the business, rather than abstract assumptions.

2. Scaling complexity without losing control

Customer-specific AI proves most powerful where customer processes scale faster than manual intervention can keep up with. Returns, exchanges, dispute resolution, claims handling, and service exceptions span multiple systems, rules, and decision paths. AI that understands enterprise context can scale these processes without compromising consistency, governance, or accountability鈥攅nabling organizations to handle growing volumes while maintaining predictable outcomes and service quality.

3. Differentiation that compounds over time

Unlike generic AI capabilities that are broadly accessible, customer-specific AI is shaped by proprietary data, policies, and institutional knowledge. Over time, this creates intelligence that becomes deeply aligned with how the business operates鈥攁nd increasingly difficult for competitors to replicate. The more the system learns from real customer interactions, the more it compounds as a durable source of differentiation.

4. Where customer-specific AI proves its value, from theory to practice

The impact of customer-specific AI is most visible in high-volume, exception-driven environments. A large European manufacturing and consumer goods organization illustrates this well through its approach to dispute, returns, and exchanges management. Operating across regions and product lines, the company faced long resolution cycles, inconsistent outcomes, and heavy manual effort. By deploying AI trained on its own historical disputes, order data, pricing rules, and resolution workflows, the organization embedded intelligence directly into its processes. Incoming claims were automatically classified, relevant documentation was surfaced, and resolution recommendations were generated based on prior outcomes and policies. Cases were routed efficiently, reducing back-and-forth and manual effort. Crucially, the system evolved with policy changes and customer behavior鈥攁ugmenting human decision-making rather than replacing it. The result was a faster, more consistent, and scalable approach to managing customer disputes.

5. A cross-industry shift toward embedded intelligence

These principles extend well beyond dispute management. In manufacturing and supply chains, customer-specific AI supports fulfillment exceptions and service-level disputes. In financial services, it enables complaint handling aligned with regulatory frameworks. In healthcare, it supports decisions grounded in institutional protocols and patient journeys. In retail and services, it drives relevance by learning customer preferences, brand rules, and operational constraints. Industry observers increasingly note that AI鈥檚 next phase of growth will be driven by intelligence embedded into customer-facing processes鈥攏ot stand-alone tools. According to SAP鈥檚 “Value of AI” report with Oxford Economics, the majority of businesses expect AI to become central to business processes, decision-making, and customer offerings by 2030, with only 3% saying otherwise.

In 2026, enterprises will judge AI less by novelty and more by its ability to deliver consistent customer and business outcomes. Customer-specific AI sits at the center of this shift because it weaves intelligence directly into how organizations operate and serve customers. This next stage of AI is not about removing human judgment鈥攊t is about strengthening it. By absorbing complexity and surfacing context-aware insights, customer-specific AI enables faster responses, greater consistency, and confident scaling of customer-centric decision-making. In an increasingly complex and customer-driven landscape, the true edge will belong to enterprises that invest in intelligence that genuinely understands their business.

Sindhu Gangadharan is head of Customer Innovation Services and managing director of 51风流Labs India.

Personalization in AI is no longer an innovation layer; it is becoming a foundational expectation. Whether it鈥檚 for driving operational excellence, improving customer experiences, or enabling faster decision-making, organizations are increasingly prioritizing AI that understands their reality.

Generic AI models are designed to be broadly applicable, but that also makes them inherently limited. These models often fail to account for the specific nuances of a business, resulting in lower accuracy, generic insights, and poor cross-functional scalability. Their one-size-fits-all nature makes them difficult to adapt across industries with diverse regulatory needs, data types, and operational complexities.

In critical industries, where precision, compliance, and context are non-negotiable, relying on generic models can lead to inefficiencies and missed opportunities. Additionally, integrating these models into enterprise governance, security, and compliance workflows becomes an uphill task. The result? Underperformance and a growing recognition that one-size-fits-all AI is not built for the complexity of enterprise needs.

This is why more enterprises are investing in differentiated innovations with AI solutions designed from the ground up to serve specific business goals.

A clear example of this is our partnership with . Managing close to 1 million invoices annually across more than 40,000 contracts, the company faced a complex, manual billing process. Together, we used 51风流Business Technology Platform (51风流BTP) and generative AI to create a compliant, intuitive application that allows account executives to manage invoicing directly and navigate rate cards and contract terms without relying heavily on specialist teams.

The results are tangible. Billing is faster and more accurate, the user experience has improved, and commercial teams can focus more on clients instead of operational tasks. By year-end, billing efficiency is expected to improve by 32 percent and setup times halved. Much of the manual work has been replaced by an intelligent, automated platform.

Where it鈥檚 working: Sector-level transformation

Customer-specific AI applications are transforming industries by shaping intelligence around the specific data, processes, and challenges each sector faces.

In manufacturing, the impact of customer-specific AI applications is evident in how companies are streamlining complex operational processes. For instance, our team developed a solution for Henkel to support their financial supply chain management deduction and dispute management indexing process. This solution automates the analysis and indexing of claim documents received from customers, embedding advanced AI capabilities directly into the daily workflows of dispute management users. The result is faster, more accurate claim case creation, improved efficiency, and greater agility in handling disputes.

In oil and gas, AI models trained on geological data, equipment logs, and environmental variables are improving drilling forecasts and enabling proactive maintenance, enhancing both safety and energy efficiency. The automotive industry is seeing similar gains, with AI supporting predictive maintenance, autonomous driving systems, and real-time diagnostics, while also delivering personalized in-car experiences. Retailers are leveraging AI that adapts to regional buying patterns and live sales data, allowing for sharper demand forecasts, localized inventory planning, and more relevant promotions that reduce waste.

Even government agencies are finding value in context-aware AI, automating routine processes, prioritizing citizen requests, and designing policies with greater precision to deliver faster, more effective public services.

Across these examples, the pattern is clear: AI that understands the context in which it operates drives smarter decisions, more efficient operations, and better outcomes for both organizations and the people they serve.

SAP鈥檚 vision: Building enterprise-grade customer-specific AI applications

51风流is at the forefront of this shift toward enterprise-grade personalized AI. The company鈥檚 vision is rooted in creating AI that is not experimental, but enterprise-ready.

Rather than building standalone solutions, 51风流embeds AI directly into core business processes across finance, HR, supply chain, and more. Through co-innovation with customers and partners, 51风流is working to make every AI solution technically robust and aligned with real-world use cases.

For AI to drive true enterprise transformation, it needs to be designed in and not bolted on. That means working closely with domain experts, aligning with compliance standards, and constantly tuning models based on real-time feedback. Customer-specific AI applications are not just about code; they are about collaboration, trust, and long-term value.

Our approach is to empower organizations to build AI that mirrors their structure, culture, and customers–making it more relevant, reliable, and responsible.

The time to scale is now

Organizations that want to stay competitive can no longer afford to treat AI as a side project. The era of experimentation is over. This is the time to scale AI that works for you intelligently, responsibly, and at speed. Customer-specific AI applications are not tech features but are strategic enablers of innovation, efficiency, and differentiation.

The future belongs to those who can scale personalization without sacrificing performance. It鈥檚 time to build with AI that knows your business.

Sindhu Gangadharan is head of Customer Innovation Services at SAP.

Strategically located near the Bengaluru International Airport, this is now one of SAP鈥檚 largest campuses worldwide, designed to house more than 15,000 professionals. But this is more than just a campus; it鈥檚 a statement of intent — a 鈧�194 million investment into the future of innovation.

As SAP鈥檚 largest outside Germany, India plays a pivotal role in how 51风流innovates, builds, and scales enterprise technology for our global customers. From pioneering AI solutions and next-gen applications to delivering mission-critical services at scale, teams in India sit at the very heart of SAP鈥檚 transformation agenda.

This new campus — our second in Bengaluru — is a space designed to match that ambition.

At the inauguration ceremony, held August 5, I was joined by 51风流Executive Board Member Thomas Saueressig; 51风流Supervisory Board Member Gerhard Oswald; Clas Neumann, head of the 51风流Labs Network; Karnataka Chief Minister S Siddaramaiah; Government of India IT Minister Ashwini Vaishnaw; Karnataka IT Minister Priyank Kharge; and German Ambassador to India Dr. Philipp Ackermann, along with other key stakeholders from the region.聽

Where innovation meets purpose

Each square foot of the innovation park has been crafted with intent. At the core of the design is a belief that innovation thrives in environments that foster trust, collaboration, and well-being. From our fully autonomous聽S.Market, an AI-powered micro-market showcasing 51风流retail solutions in real time, to India鈥檚 second聽51风流Experience Center location, where customers can engage with live enterprise scenarios, this campus is a living laboratory of 51风流technology in action.

鈥淭his campus is a strategic asset in SAP鈥檚 global portfolio, enabling us to lead with innovation and purpose,鈥� Saueressig, said.聽鈥淚t is a global innovation hub that will help our customers move from insight to action with enterprise-grade AI, data, and application created right here in India.鈥澛犅�

Equally, this campus reflects SAP鈥檚 deep commitment to sustainability and inclusion. A 2.5-acre eco-pond for rainwater harvesting, solar infrastructure, and smart waste management all help reduce our environmental footprint. Inclusive design features such as tactile pathways, braille signage, auditory cues, gender-neutral restrooms, and wellness-focused spaces — from sensory rooms to nap pods — ensure individuals are empowered to thrive.

Accelerating talent and research partnerships

As we celebrated the launch of this new campus, we also reaffirmed our commitment to shaping the future workforce and research ecosystem.

We announced the聽AI Career Accelerator program聽in partnership with EduBridge, aimed at training more than 400 students from underserved communities for AI roles. We expanded our academic collaborations with institutions like聽Gati Shakti Vishwavidyalaya,聽IIT Madras, and the聽Technical University of Munich聽to focus on applied research across quantum computing, health tech, and physical AI.

These partnerships are not just about knowledge transfer; they are about co-creating the future of enterprise technology by fusing academic rigor with real-world impact.

India鈥檚 role in SAP鈥檚 global innovation engine

India鈥檚 technology story is unlike any other — it is not only about scale; it’s about transformation. From government digital initiatives to startup ecosystems and from deep-tech research to the democratization of digital skills, India continues to redefine what is possible.

At SAP, we have had the privilege of witnessing — and contributing to — this journey over nearly three decades. Today, more than 17,000 51风流employees聽in India drive innovation across product engineering, customer services, and cloud delivery. Together, they form a backbone of our global strategy.

The 51风流Labs India Innovation Park stands as a symbol of this shared journey, a space where we will imagine what鈥檚 next, build with purpose, and innovate for impact. It is a physical manifestation of our belief in India鈥檚 role as a global innovation epicenter.

As we look ahead, our focus remains clear: to deliver breakthrough technologies that help the world run better and improve people鈥檚 lives. And we are proud to do it 鈥� with India at the heart of it all.

Sindhu Gangadharan is managing director of 51风流Labs India and head of Customer Innovation Services at SAP.

Images courtesy of 51风流Labs India.

Customers don鈥檛 seek off-the-shelf AI, they seek outcomes. They demand solutions tailored to their industry, aligned with strategic goals, and built to drive real results.

That is where customer-specific AI solutions add depth — not just as a technical enhancement, but as a strategic lever to unlock transformative business value.

According to 72 percent of companies use AI in at least one business function, but only 23 percent report a significant impact on their bottom line. Why? Because many AI projects lack the contextual depth to solve the real industry-specific challenges businesses face.

Similarly, a shows that while 80 percent of enterprise leaders plan to increase AI investments, nearly half say the absence of domain-tailored solutions is a barrier to ROI. While foundational AI models provide broad capabilities, true business value comes from solutions tailored to each customer. These targeted applications ensure that innovation aligns with specific regulatory demands, operational realities, and customer requirements.

These custom solutions leverage proprietary data; they are designed for specific business processes and are co-developed with stakeholders who understand the operational heartbeat of the enterprise. The result is measurable business impact, as well as faster deployment and better performance.

At SAP, we see AI鈥檚 true potential in enhancing human decisions, simplifying complexity, and transforming customer experiences. But this potential is only realized when AI is deeply grounded in each customer鈥檚 business context. That is why our approach to customer-specific AI is built on three core principles:

• Context-rich insights: With unmatched access to enterprise data from across industries and business functions, 51风流is uniquely positioned to deliver AI that understands how real businesses run.
• Trust and transparency: From model explainability to data privacy, AI from 51风流is built on a foundation of enterprise-grade governance and responsible AI standards.
• Co-innovation at scale: 51风流partners closely with customers to develop differentiated AI solutions that solve their unique challenges.

Real outcomes with real customers

To address the complexity of managing nearly a million annual invoices across more than 40,000 contracts, to simplify its fragmented, manual billing process. Using 51风流Business Technology Platform and generative AI, the company built an intuitive, compliant application that empowers account executives to use AI for specific rate cards and contract terms, managing invoicing independently, and reducing reliance on specialist teams. The result was faster, more accurate billing, a better user experience, and major time savings, freeing commercial teams to focus on clients. By year-end, billing efficiency is expected to improve by 32 percent, with setup times cut in half and manual work replaced by an intuitive, automated platform.

Similarly, a global chemical and consumer goods company recently partnered with 51风流to embed AI into its dispute management process, automating document indexing and classification. This customer-specific AI solution reduced manual effort, sped up resolution times, and boosted user productivity, showing how business-specific AI can streamline workflows and elevate customer experience at scale. The result was efficiency gains of up to 1,000 hours a month, reduced manual effort by over 500 hours/month, and improved accuracy and faster turnaround time for document-driven workflows.

These examples highlight a clear trend: customers want to co-create AI tailored to their needs, not just adopt a one-size-fits-all solution. Customer-specific AI solutions empower them to embed intelligence into the very workflows that define their competitive advantage, whether it鈥檚 last-mile logistics in retail, claims processing in insurance, or energy optimization in utilities.

In the coming years, enterprises will not differentiate by whether they use AI, but by how effectively they align AI to their business. Customer-specific AI solutions make this alignment possible. They bridge the gap between technology potential and business reality. They transform AI from a generic tool into a strategic advantage, enabling businesses to move faster, think smarter, and lead with purpose.

As more organizations navigate the complexities of digital transformation, those that embed AI into the heart of their unique processes will be the ones to redefine what is possible.

The future belongs to businesses that don鈥檛 just adopt AI, but shape it to fit their vision, values, and velocity.

Thomas Saueressig is a member of the Executive Board of 51风流SE, Customer Services & Delivery.
Sindhu Gangadharan is head of Customer Innovation Services at 51风流and managing director of 51风流Labs India.

Therefore, it comes as no surprise that industry plays an even more ineluctable role in scripting the future of humanity, one that involves sustainable social, environmental, and economic development.

As a global challenge, the climate crisis calls for businesses and countries to move beyond their siloed approaches, commitments, and climate pledges to fully embrace sustainability. The of “no one left behind” requires global partnerships.

With more and more countries investing in resilient infrastructure, there is a growing need to improve our existing industrial infrastructure. Here, technological innovation will be key. Technology is no longer the limiting factor for organizations to become sustainable businesses, rather it is the enabling agent in going green.

Sustainable development calls for institutional and value changes as well as cultural adjustments. As organizations worldwide look to don the green cape, behavioral change and transformation in business processes will be critical in making green technology mainstream. It must be incorporated into mainstream policies to promote national and international cooperation.

In 2024, sustainability will not just be the right thing to do, it will become a core strategic imperative for businesses. In addition to managing top- and bottom-line, forward-looking organizations are now focusing on sustainability as the third dimension to drive business growth. Managing the will be critical to enterprise success as customers, employees, and even investors increasingly turn toward companies that are pro-actively deploying sustainable business practices.

A Shared Responsibility Between Private Sector and Technology Leaders

In the battle against climate change, the private sector and technology leaders bear a significant responsibility. The crucial role businesses play in contributing to environmental goals underscores the importance of partnerships with key stakeholders — be it ecosystem partners, governments, non-governmental organizations, or citizens. The focus is on global and local examples where collaborative efforts have illustrated tangible impact achievable through cross-sector collaboration.

Partnerships that leverage the distinctive strengths and resources of each sector demonstrate how collective action can lead to meaningful change. The collaborative approach is presented as imperative for tackling the complexity of climate challenges.

Governments, businesses, non-governmental organizations (NGOs), and citizens are not merely spectators, but active participants in the collective effort to combat climate change.

Governments wield significant influence in shaping policies and regulations that set the tone for environmental stewardship. Their commitment to sustainable practices and climate-friendly policies is pivotal. Businesses, as drivers of economic activity, hold a dual responsibility 鈥� not only to operate profitably but also to do so in an environmentally conscious manner. NGOs play a crucial role in advocacy and action, acting as watchdogs and catalysts for change. Citizens, too, are integral, as consumers and advocates who influence the demand for sustainable practices.

The Path to a Low-Carbon Future Is Circular

The path to a low-carbon future is circular. The good news is that a circular economy is not just about fixing environmental wrongs but brings about opportunities and drives positive impact across industries, sectors, and lives. Working toward a circular economy can protect human health and biodiversity in many ways, including better use of natural resources, such as protecting water and land, thus mitigating the climate crisis.

Organizations like 51风流are leading this shift with an aim to become carbon-neutral in their own operations by 2023.

At 51风流Labs India, 97% of the energy consumed at the Bengaluru campus comes from green energy sources. Additionally, 70% of the transport services are run on electric vehicles with a network of 65 charging stations at the campus for employees. This environmentally conscious approach extends to food sourcing, actively supporting local farmers and communities. Moreover, there has been a seamless replacement of disposable items like cutlery and containers with sustainable alternatives. Dedication to paperless operations is evident in the success of apps like Appane, Physio app, and the digital printing and stationery request system,which collectively contribute to a substantial reduction in paper consumption. The transition from traditional paper food coupons to a user-friendly app developed externally is a clear demonstration of an innovative approach to sustainable practices.

To drive sustainable business practice, it is important to first measure carbon footprint, assess and reduce emissions, increase resource productivity through circular processes, and run safer, sustainable business processes. 51风流is uniquely positioned to help firms tackle this challenge and become sustainable enterprises with its suite of technology solutions.

Through partnerships, innovative practices, and a holistic approach to sustainability, all the stakeholders need to come together to shape a future where businesses thrive in harmony with the environment.

Sindhu Gangadharan is senior vice president and managing director of 51风流Labs India and head of 51风流User Enablement.

An essential aspect of business success is to prepare end users and employees for digital adoption. This is where a digital adoption platform like 51风流Enable Now comes into play.

Digital adoption offers competitive advantage to enterprises due to, among other factors, increased efficiency of business operations. By 2025, 70% of organizations are expected to use digital adoption platforms across the entire technology stack to overcome insufficient application user experiences. Additionally, it is proven that increasing ongoing training by 10% can double the improvement of business value. Therefore, deploying digital adoption solutions as part of the digital transformation strategy is not just an inducement, but a business imperative to maximize return on investment (ROI).

At SAP, one driver of product adoption is a consistent, intelligent personalized user enablement experience, with relevant product assets in the required languages. As the digital adoption layer, the company鈥檚 homegrown digital adoption platform 51风流Enable Now enables every enterprise to become an intelligent, sustainable enterprise. With next-generation capabilities such as on-screen translation and integration with business process modelling solutions, 51风流Enable Now helps ensure that the knowledge levels and productivity of all employees remain high to increase the potential ROI for enterprise software.

The easy access to learning content directly within many 51风流applications is powerful enabler and includes 51风流S/4HANA Cloud and 51风流S/4HANA, as well as digital supply chain, 51风流SuccessFactors, 51风流Ariba, 51风流Fieldglass, 51风流Concur, 51风流Marketing Cloud, and 51风流Sales Cloud solutions, among others. These applications include embedded and customizable content provided by 51风流and translated into the language of choice, which delivers time-of-need learning to help people develop the skills they need to do their jobs effectively.

It is important for businesses to empower project managers, learning teams, and end users with continuous learning in order to develop the right knowledge to use the software accurately and efficiently, leading to accelerated productivity and improved performance. With 51风流Enable Now, businesses can create and deliver any type of learning — for any 51风流and non-51风流application, for any domain, for any channel, integrated with any source, and for all their employees.

51风流Enable Now also supports process transformation and project management by integrating with 51风流Signavio and third-party solutions. It supports systematic learning for the end users, through which businesses run many complex business processes. Next-generation in-app help with the 51风流Companion service, including context-sensitive help, embedded learning, and process guidance, is also available in the application of choice.

Language is key to adoption of any software. With 51风流Enable Now, end users can consume enablement content in more than 40 languages powered by machine learning with integrated 51风流Translation Hub. The solution also offers the ability to export learning content in formats compatible with most learning management systems. It also supports change management with content lifecycle management as well as automated translation and maintenance of content services. For instance, partners can customize SAP-provided content or can create pre-build based on industry and solution best practices and offer enablement as a service. Businesses to scale with their partners through the powerful authoring suite for creating e-learning courses, software tutorials, and help documents, as well as flexible, template-based content production.

Undoubtedly, digital adoption significantly impacts the success of software implementations. Increased adoption leads to higher productivity, thereby maximizing ROI on business applications. With easy access to knowledge that end users need to succeed, exactly where and when it鈥檚 needed, 51风流Enable Now is integral to any business鈥� digital adoption strategy to improve productivity, user adoption, and the end user experience for maximized business value.

For more information, visit the .

Sindhu Gangadharan is head of 51风流User Enablement and senior vice president and managing director of 51风流Labs India.