Conversational AI Ecosystem Focus on Technology Partners | Market Insights™
November 5, 2024
Conversational AI
Conversational AI
The enterprise landscape is on the cusp of a transformative era, with the emergence of gen AI (generative artificial intelligence).
This technology, capable of creating entirely new content, promises to revolutionize countless workflows and redefine enterprise operations.
Generative AI’s integration into platforms such as SAP, Oracle, Microsoft, Salesforce, and Pega is not merely a trend but a fundamental shift in how enterprises will innovate and operate.
Reach out to discuss this topic in depth.
Enterprises today face a critical decision when considering generative AI adoption: whether to opt for point solutions or a platform-led approach. This decision is crucial as any such investment demands substantial investment.
While many enterprises initially gravitate towards point solutions, deploying isolated instances of large language models (LLMs) for specific features, this fragmented approach has limitations. Generative AI models are typically trained for broad, personal usage rather than enterprise-specific applications, which can limit their effectiveness in enterprise scenarios.
On the other hand, platform-embedded solutions such as SAP Joule, Microsoft Copilot, Oracle Digital Assistant, Salesforce Einstein and others, are not only more relevant but also easier to scale adopt. Think of it as having a mini-AI (artificial intelligence) assistant built right into your familiar software, empowering you to leverage its power without needing extensive technical expertise.
Our recent interactions with enterprises revealed that 70% of enterprises are prioritizing platform-embedded generative AI as a key strategy for digital transformation. This approach not only simplifies AI deployment, but also enhances productivity and operational efficiency, making it a compelling choice for forward-thinking organizations.
By integrating Gen AI capabilities directly into existing enterprise platforms, enterprises are benefiting from:
Integrated operational environment – Platform-embedded AI seamlessly integrates into existing business systems (enterprise resource planning (ERP), customer relationship management (CRM), human capital management (HCM), and others), ensuring consistent AI-driven insights across all functions. This integration reduces disruptions and fosters a cohesive operational environment, in which data flows effortlessly between applications, maximizing the utility of AI insights
Enhanced data utilization – Embedded AI has access to enterprise-wide data, generating more accurate and holistic insights. It ensures seamless data exchange and integration across applications, making AI insights more valuable and actionable compared to point solutions limited to specific data sets
Futureproofing innovation – Adopting platform-embedded AI aligns enterprises with the strategic roadmap of leading software providers, ensuring access to the latest AI advancements and innovations
Higher cost efficiency – Platform-embedded AI leverages existing infrastructure, reducing the need for additional hardware, software, and technical expertise, offering more cost-effective AI capabilities. This consolidation leads to a lower total cost of ownership (TCO), by avoiding the costs associated with deploying and maintaining multiple standalone AI solutions
Reduced complexity – Embedding generative AI within enterprise platforms simplifies deployment and usage. Unlike traditional AI implementations that require extensive setup, platform-embedded AI integrates into daily-use software, reducing the need for specialized technical expertise, accelerating implementation timelines, and minimizing workflow disruptions
Despite the enthusiasm, enterprises adopting the platform-embedded gen AI approach should take care of challenges associated such as:
Enterprise readiness – Integrating Gen AI into existing platforms can be complex and requires significant investment in technology and skills. Enterprises should conduct a thorough assessment of their current infrastructure and capabilities, and consider partnering with experienced AI vendors to streamline the integration process and mitigate risks
Skill gaps – There is a high shortage of professionals within the data, AI, ERP and CRM sector, with these workers needing the skills to develop and maintain gen AI solutions. Enterprises need to invest in training and development programs to upskill existing employees or can consider hiring new resources and collaborating with educational institutions to build talent
Ethical and regulatory compliance – Businesses must navigate the ethical implications of AI, such as bias and fairness, to build trust with their users. Establishing a dedicated ethics committee to oversee AI initiatives, performing regular audits and implementing bias detection algorithms are crucial ways to maintain fairness and transparency
Data security and privacy – Platform-embedded AI relies on vast amounts of data, raising concerns about data security and privacy. Enterprises must adopt robust data security measures such as encryption, access controls, and regular security audits and ensure compliance with data protection regulations such as general data protection regulation (GDPR) and California consumer privacy act (CCPA)
Change management and adoption – Ensuring that employees adapt to new AI-driven processes and tools can be difficult. Also, resistance to change and a lack of understanding of AI capabilities can impede successful adoption. Thus, implementing a comprehensive change management strategy that includes clear communication, training programs, and user support remains a must
Adoption trends and future outlook
While the adoption of platform-embedded generative AI is gaining momentum across various enterprises, solutions like Joule, Copilot, and Einstein are witnessing increased uptake, driven by their ability to enhance productivity, efficiency, and decision-making.
Enterprises are now tailoring these AI functionalities to their specific needs, integrating them seamlessly with existing business processes within platforms such as SAP BTP. This customization ensures that AI solutions are closely aligned with unique workflows, improving decision-making and automating routine tasks.
As businesses grow, the scalable infrastructure provided by platforms supports the expanding adoption of generative AI, allowing for increased data handling and more complex AI models. Future trends indicate even greater collaboration between AI developers and business units, driving innovation and creating new use cases. This will ensure that enterprises remain at the forefront of AI-driven transformation, leveraging advanced analytics and intuitive AI interfaces to maintain a competitive edge in their respective industries.
By understanding and harnessing the trends within platform landscape, enterprises can position themselves at the forefront of AI-driven transformation, reaping the benefits of enhanced productivity, efficiency, and strategic decision-making.
If you found this blog interesting, check out our recent blog focusing on What Recent Generative AI Updates And Announcements Signal For Some Industries | Blog – Everest Group (everestgrp.com)
At Everest Group, we are closely tracking the generative AI evolution in enterprise platforms. To discuss this topic more with our team, please reach out Abhishek Mundra or Vinisha Choudhary.
What impact will Salesforce’s upcoming global partnership with IQVIA have? Get the expert view here, or get in touch to understand how this significant move in the life sciences CRM sector might impact your business.
Once again, the winds of change are blowing in the life sciences CRM landscape. The usual suspect, Salesforce, has announced its strategic global partnership with IQVIA to enhance the capabilities of its Life Sciences Cloud.
This is noteworthy, more so in the backdrop of the Veeva and Salesforce separation in 2022, where Veeva fully embraced its home-brewed offering, Veeva Vault. The Salesforce-IQVIA partnership marks a significant move in Salesforce’s commitment to delivering robust life sciences customer engagement solutions.
However, whether this move will truly propel Salesforce to the industry apex remains to be seen. Veeva has already established itself as the go-to solution for life sciences enterprises; on the other hand, Salesforce carries the baggage of being a jack-of-all-trades, master of some in the customer engagement arena. The hiring of Frank Defesche – a former Veeva executive – by Salesforce to lead its life sciences division is one of several initiatives that drives home the point that the battle for market leadership is going to be fierce.
Historically, Veeva has been at loggerheads with both CRM incumbents: IQVIA (Veeva’s Antitrust Lawsuit against IQVIA) and Salesforce (halting its partnership with Salesforce Cloud). However, currently, IQVIA and Salesforce have allied to confront the Customer Engagement Platform (CEP) market. This partnership brings forth several prospects and pitfalls, as illustrated in the exhibit below:
Prospects: While IQVIA continues to lead the market in life sciences data management, it faces formidable competition from Veeva. However, the recent collaboration between IQVIA and Salesforce has fostered innovation and equipped Salesforce with data management expertise to leverage. Furthermore, this partnership extends Salesforce’s customer engagement market influence by granting access to IQVIA’s clientele. By integrating the data and analytics of IQVIA with the powerful CEP of Salesforce, the partnership promises a holistic overview of customer interaction and insights. This potential end-to-end, industry-specific solution will go on to streamline operations and efficiency through integrated systems and workflows.
Pitfalls: As the IQVIA-Salesforce transition gradually unfolds until 2029, they will encounter increased expenses for training, upskilling, onboarding, and more operational processes. Integrating existing legacy systems with the new IQVIA-Salesforce solutions will be challenging. Changing the status-quo will require a relook at data privacy and regulatory compliance by enterprises, which can be quite resource-intensive. The partnership also adds an uncertainty variable, as transitioning from the existing CRM may lead to concerns around the overall impact on business operations and workflows. As enterprises transition to the new system, there will be a risk of data migration, system downtime, and a potential loss to business. Currently, the Salesforce customer engagement platform is distinguished by its premium licensing fees, which might further increase due to the ongoing partnership. While this presents opportunities for SIs for project management endeavors, the new Salesforce Life Sciences Cloud should still demonstrate its value.
The world of CRM is seeing a gigantic wave of customer-centricity, and service providers who still hold on to horizontal approaches will be swept under it. The days of a one-size-fits-all solution are over; now, enterprises seek solutions that can withstand the ever-changing dynamics of the market with technological and operational flexibility. Service providers must look beyond consultation and implementation by taking up change management initiatives that deliver long-term value for their clients. They are expected to stay abreast of the latest developments, and provide solutions tailored to the unique needs of enterprises.
Service providers will play a critical role in strategic consulting, data migration, implementation, customization, and ongoing support to ensure smooth transitions for enterprises adopting new customer engagement systems. It can cash in on these opportunities by monetizing various aspects of the collaboration, as elaborated below:
Enterprises are weighing their options carefully as the life sciences CRM market continues to evolve in its trajectory. The three broad options for enterprises are as follows:
This partnership signifies the eventual departure of IQVIA from the competition by the decade’s end, leaving only two dominant incumbents, Veeva and Salesforce, in the market. Presently, Veeva commands the lion’s share of the life sciences CRM market, but this landscape is expected to evolve in the years ahead. Additional implications within the CRM market are depicted in the exhibit below:
With the life sciences commercial landscape evolving consistently and the ongoing evolution of Generative AI technology, the pace of innovation is frenetic within the life sciences industry. This rapid progress is also giving rise to a new wave of specialized providers catering to niche needs. Consequently, enterprises must continuously assess the evolving landscape of commercial technology offerings and augment their tech infrastructure accordingly.
If you have questions about the life sciences IQVIA’s extended partnership with Salesforce or would like to discuss developments in the life sciences commercial space, please reach out to [email protected] or [email protected] or [email protected]. For a deeper understanding of the shift to next-gen customer products in the life sciences sector, read our blog.
Watch our discussion on the critical shift from CRM ecosystems to CX platforms in our session, Key Insights: The Evolving Commercial Technology Landscape in Life Sciences.
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