Techaisle Blog

On 24^th September 2024, Google Cloud unveiled several significant updates to its AI offerings. These updates include enhancements to the Gemini model, including the general availability of a two million token context window for Gemini 1.5 Pro, improvements in provisioned throughput, advancements in grounding capabilities, and the general availability of the Imagen 3 text-to-image generation model. These new product announcements from Google Cloud highlight its commitment to advancing AI technologies and providing businesses with the tools they need to drive innovation and growth. With these new features, Google Cloud further solidifies its position as a leader in AI development.

Google also discussed the evolution of its agents, highlighting how they have become increasingly sophisticated and capable over time. As AI technology has advanced, Google's agents have evolved from simple chatbots to intelligent assistants that can perform complex tasks and provide valuable insights. Cloud agents are intelligent software applications that can perform tasks autonomously or in collaboration with humans. They leverage artificial intelligence and machine learning to automate processes, analyze data, and provide insights. Google Cloud has released a variety of agents, including customer agents, employee agents, data agents, security agents, and creative agents. These agents offer numerous benefits, such as increased efficiency, improved decision-making, enhanced customer satisfaction, and reduced operational costs. Google Cloud agents differentiate themselves by integrating with Google's AI platform, Vertex AI, which simplifies development and deployment. Additionally, Google Cloud's agents are designed to be scalable, reliable, and secure, ensuring that businesses can leverage AI to meet their evolving needs.

Gemini Updates and Expanded Capabilities

Updates to the Gemini Model: One of the event's key highlights was the announcement of updates to the Gemini model. The Gemini model, known for its powerful generative AI capabilities, has been further enhanced to provide even more robust performance. The updates to the Gemini Model, specifically the introduction of the Gemini 002 version, bring several advantages for customers. The new version is available in both Flash and Pro versions. The Flash version is designed for speed and versatility, making it suitable for a wide range of applications. On the other hand, the Pro version offers incremental reasoning capabilities, which can be particularly beneficial for more complex tasks that require deeper analysis and understanding. The context window for Gemini 1.5 Pro has also been expanded to 2 million tokens. This significant increase allows for analyzing larger amounts of data in a single prompt, such as two hours of video or 1500 pages of text. This capability enables customers to process and analyze extensive datasets more efficiently, leading to more comprehensive insights and better decision-making.

Customer experience has become a key differentiator in today's competitive market, particularly for SMBs and midmarket firms. These companies, often with limited resources, are increasingly adopting contact center solutions to improve customer interactions and build loyalty.

Recent research by Techaisle, covering 2400 SMBs and Midmarket firms, indicates that 44% of small and medium-sized businesses (SMBs) and 48% of upper midmarket firms are prioritizing investments in customer experience (CX) solutions. Additionally, 55% of SMBs are either migrating their contact center to the cloud or planning to do so. In contrast, 32% of upper midmarket firms plan to use cloud contact center solutions. This trend underscores the growing recognition of the importance of delivering excellent customer service in a digital-first world.

Key Investment Areas for SMB and Midmarket Contact Centers

SMBs are investing heavily in contact center technologies to improve their CX capabilities. The research highlights the following areas as top priorities:

• IVR Voice, Video, Chat, Network Performance: A majority of SMBs (56%) are investing in technologies that enable seamless and efficient communication channels. This includes interactive voice response (IVR) systems, video conferencing, live chat, and robust network infrastructure. By automating routine tasks, IVR can improve efficiency and free up human agents to handle more complex issues. This enhances customer experience and reduces operational costs and staffing needs. Additionally, IVR systems can scale to accommodate growing call volume and provide insightful data for process improvement. Despite the benefits, implementing an effective IVR system can present challenges. The initial investment is a barrier for some SMBs, and designing a complex system has been daunting. Moreover, a poorly designed IVR system has frustrated SMB customers and damaged the brand. Integrating IVR with existing systems has also been challenging, and ongoing maintenance required to ensure proper functioning has been complex.
• AI Insights/Analytics for Agents: Leveraging artificial intelligence (AI) to provide agents with valuable insights and analytics is a crucial focus for 50% of SMBs. They feel that GenAI offers significant benefits in the context of contact center operations. SMBs and midmarket firms firmly believe that AI-powered tools will help agents better understand customer needs, resolve issues more efficiently, and personalize interactions. This leads to improved customer satisfaction and contributes to overall business growth and success. However, for early adopters, implementing AI insights has challenged SMBs despite its advantages. The initial investment in AI technology and the need for skilled personnel to manage and interpret the data have been barriers. Additionally, ensuring data quality and privacy is proving complex, and integrating AI tools with existing systems requires technical expertise. Moreover, the ongoing maintenance and updates of AI models to adapt to changing business needs and customer behaviors are unpredictable and time-consuming.
• App Integrations / CRM Integration: Integrating contact center solutions with other business applications, such as customer relationship management (CRM) systems, is vital for delivering a unified customer view. 47% of SMBs are prioritizing this integration. By merging contact center solutions with CRM systems and other business applications, SMBs hope to achieve a comprehensive and cohesive view of their customers. This integration facilitates seamless information sharing, mitigates data silos, and enhances customer service. With access to a complete customer profile, agents can provide more personalized and efficient support, heightening customer satisfaction and loyalty. Despite these significant benefits, integrating applications and CRM systems poses challenges for SMBs. The complexity of combining different systems, issues with data compatibility, and potential security risks have complicated implementation. Additionally, ensuring data accuracy and consistency across various platforms has been time-consuming and resource-intensive. Furthermore, the ongoing maintenance and updates required to keep integrations running smoothly necessitate technical expertise and time.

Must-Have Features for SMB Contact Center Solutions

To meet the evolving needs of SMBs and midmarket firms, contact center solutions must offer a range of essential features. The Techaisle research identifies the following as the most sought-after features:

Xerox, synonymous with photocopying, has embarked on a bold transformation to remain relevant in the digital age. From its humble beginnings as a copier manufacturer to its status as a diversified technology services company, Xerox's journey is a testament to its resilience and adaptability. Groundbreaking innovations punctuate Xerox's history. The introduction of the plain paper copier in the 1950s revolutionized document reproduction, and the company's subsequent development of the graphical user interface (GUI) and computer mouse laid the foundation for modern computing. The laser printer, another Xerox invention, further cemented its position as a technology pioneer. However, the rise of digital technology and the decline of traditional printing posed significant challenges to the company.  Xerox began a strategic shift towards IT Services with the 2010 acquisition of Affiliated Computer Services (ACS), rebranded as “Conduent” and spun off as a separate business services division in 2016.  The COVID-19 pandemic accelerated the shift towards remote work and digital document management.  While Xerox saw a decline in traditional office printing, it also identified new opportunities in emerging segments, demonstrating its agility and forward-thinking approach, which should give us all optimism about its future. 

It was my great pleasure to speak with John G. Bruno, Xerox's President and Chief Operating Officer. The conversation covered a broad array of subjects, focusing on Xerox's strategy for Reinvention. 

The traditional office environment has undergone a seismic shift with the rise of remote and hybrid work models. Once synonymous with physical document management, Xerox is adapting to this new reality by strategically balancing the preservation of its core print business with a bold venture into Digital Services and IT Services. While print remains a critical component of Xerox's operations, the company recognizes the growing demand for digital tools. It is investing heavily in technologies that can extract value from documents in a digital format. 

Xerox's foray into digital services is driven by the understanding that information is increasingly digitized. The company is developing services to capture, process, and analyze content from various sources, including physical documents. By doing so, Xerox aims to position itself as a trusted partner for businesses seeking to optimize their document workflows and extract valuable insights from their data. 

Furthermore, Xerox is expanding its service offerings to include IT services, particularly for small and medium-sized businesses. By providing a comprehensive suite of IT services, including managed security and cloud solutions, Xerox is addressing the growing technology needs of this market segment. This strategic move diversifies the company's revenue streams and strengthens client relationships. In essence, Xerox is evolving from a hardware-centric company to a technology-driven organization that empowers businesses to navigate the digital landscape. 

The company's Reinvention strategy is threefold. This three-pronged approach demonstrates Xerox's commitment to preserving its core print business, simplifying its operations to improve the client and employee experience, and capitalizing on the opportunities presented by the digital revolution. 

1. Strengthening the Core Print Business:

Xerox aims to maintain its leadership in the print industry by focusing on efficiency and productivity, reducing costs, and capturing growing segments like home office printing and production print. Despite the rise of digital platforms, print remains a significant market, and Xerox is determined to solidify its position as a leader in this space. As remote work and hybrid work models become the norm, the demand for home printers is expected to rise. Xerox is positioning itself to capitalize on this trend by offering high-quality, user-friendly printers to address the evolving needs of hybrid workers.   On the other end of the spectrum, Xerox also focuses on production print. This segment caters to businesses with high-volume printing needs, such as publishing houses, advertising agencies, and direct mail companies. Xerox aims to increase its market share in this lucrative sector by investing in advanced printing technologies and workflow solutions. 

2. Driving Efficiency and Growth through Global Business Services:

A key component of the Xerox Reinvention is the formation of a new Global Business Services organization. By centralizing internal processes and leveraging shared capabilities, Xerox aims to simplify operations, reduce costs, and improve the overall client and employee experience. This, in turn, frees up resources for investment in growth areas, such as emerging technologies and digital services. As Xerox continues to evolve, the Global Business Services organization will play a pivotal role in ensuring the company's long-term success. 

3. Expanding into Digital Services and IT Services:

Recognizing the digital transformation, Xerox is investing heavily in digital services, including intelligent document processing, content management, and data capture. The company also sees significant potential in IT services, particularly for small and medium-sized businesses. Recognizing the inevitable shift towards digitalization, Xerox is increasingly investing in digital services. At the heart of this strategy is intelligent document processing, which involves extracting valuable information from physical and digital documents. This technology is crucial for businesses looking to automate workflows, improve efficiency, and gain insights from their data. In addition to document processing, Xerox is focusing on customer engagement services, whereby Xerox helps companies utilize proprietary content to more effectively target and communicate with their customers, even designing and implementing omnichannel marketing campaigns. Xerox entered the IT services market to expand its digital footprint, particularly targeting small and medium-sized businesses (SMBs). By offering a range of IT services, including managed security, cloud solutions, and technical support, Xerox aims to become a one-stop shop for SMBs' technology needs. 

The landscape of GenAI is rapidly evolving, and midmarket firms are striving to keep pace with this change. New data from Techaisle (SMB/Midmarket AI Adoption Trends Research) sheds light on a fascinating trend: adopting multiple large language models (LLMs), an average of 2.2, by core and upper midmarket firms. Data also shows that 36% of midmarket firms are piloting with an average of 3.5 LLMs, and another 24% will likely add another 2.2 LLMs within the year.

The survey reveals a preference for established players like OpenAI, with a projected penetration rate of 89% within the midmarket firms currently adopting GenAI. Google Gemini is close behind, with an expected adoption rate of 78%. However, the data also paints a picture of a dynamic market. Anthropic is experiencing explosive growth, with an anticipated adoption growth rate of 100% and 173% in the upper and core midmarket segments, respectively. A recent catalyst in midmarket interest for Anthropic is the availability of Anthropic’s Claude 3.5 Sonnet in Amazon Bedrock.

This trend towards multi-model adoption signifies a crucial step – midmarket firms are no longer looking for a one-size-fits-all LLM solution. They are actively exploring the functionalities offered by various models to optimize their specific needs.

However, the data also raises questions about the long-term sustainability of this model proliferation due to higher costs, demand for engineering resources (double-bubble shocks), integration challenges, and security. Additionally, market saturation might become a challenge with several players offering overlapping capabilities. Only time will tell which models will endure and which will fall by the wayside.

Furthermore, the survey highlights a rising interest in custom-built LLMs. An increasing portion of midmarket firms (11% in core and 25% in upper) will likely explore this avenue. In a corresponding study of partners, Techaisle data shows that 52% of partners offering GenAI solutions anticipate building custom LLMs, and 64% are building SLMs for their clients, indicating a potential shift towards smaller specialized solutions.

Why Multi-Model Makes Sense for Midmarket Firms

The journey from experimentation to full-fledged adoption requires a strategic approach, and many midmarket firms are discovering the need to experiment with and utilize multiple GenAI models. There are several compelling reasons why midmarket firms believe that a multi-model strategy might be ideal:

Specificity and Optimization: Various LLMs specialize in different tasks. Midmarket firms believe they can benefit from a multi-model strategy, using the best-suited model for each purpose. This may enhance efficiency and precision across a broad spectrum of use cases. Since GenAI can reflect biases from its training data, a multi-model approach also serves as a safeguard. Combining models informed by diverse datasets and viewpoints ensures a more equitable and efficient result.

Future-Proofing: LLMs are rapidly advancing, offering a stream of new features. Without a visible roadmap from LLM providers, midmarket firms hope to benefit from using various models to stay current with these innovations and remain flexible in a dynamic market. As business requirements shift, a diversified model strategy enables modification of their GenAI tactics to align with evolving needs. This strategy permits businesses to expand specific models to meet increasing demands or retire outdated ones as necessary.

Despite the benefits, midmarket firms are also experiencing challenges

High Cost: LLMs have a high price tag, particularly for smaller midmarket companies. Creating and maintaining an environment that supports multiple models leads to a substantial rise in operational expenses. Therefore, a small percentage of midmarket firms are conducting a thorough cost-benefit analysis for every model and optimizing the distribution of resources to ensure financial viability over time. Managing and maintaining multiple LLMs is time-consuming, as different models have varying data formats, APIs, and workflows. Developing a standardized approach to LLM utilization across the organization has been challenging, and a lack of engineering resources has surfaced.

Specialized Skills: Deploying and leveraging multiple LLMs necessitates specialized skills and knowledge. To fully capitalize on the capabilities of a diverse GenAI system, it is essential to have a team skilled in choosing suitable models, customizing their training, and integrating them effectively. Midmarket firms are investing in training for their current employees or onboarding new specialists proficient in LLMs.

Integration Challenges: Adopting a multi-model system has benefits but can complicate the integration process. Midmarket firms are challenged to craft a comprehensive strategy to incorporate various models into their current workflow and data systems. The complexity of administering and merging numerous GenAI models necessitates a solid infrastructure and technical know-how to maintain consistent interaction and data exchange among the models.

Midmarket Firms Intend to Adopt DataOps to Develop GenAI Solutions Economically

While large enterprises have shown how effective DevOps can be for traditional app development and deployment, midmarket firms notice that conventional DevOps approaches may not fit as well for emerging AI-powered use cases or GenAI. Techaisle data shows that only half of the midmarket firms currently have the necessary talent in AI/ML, DevOps, hybrid cloud, and app modernization. Although DevOps is great for improving the software lifecycle, the distinct set of demands introduced by GenAI, primarily due to its dependence on LLMs, poses new hurdles.

A primary focus for midmarket firms is ensuring a steady user experience (UX) despite updates to the foundational model. Unlike conventional software with updates that may add new features or bug fixes, LLMs are built to learn and enhance their main functions over time. As a result, while the user interface may stay unchanged, the LLM that drives the application is regularly advancing. However, changing and or even swapping out these models can be expensive.

DataOps and AnalyticsOps have emerged as essential methodologies tailored to enhance the creation and deployment of data-centric applications, much like those powered by GenAI. DataOps emphasizes efficient data management throughout development, ensuring the data is clean, precise, and current to train LLMs effectively. Conversely, AnalyticsOps concentrates on the ongoing evaluation and optimization of the GenAI applications' real-world performance. Through persistent oversight surrounding user interaction, DataOps and AnalyticsOps empower midmarket firms to pinpoint potential enhancements within the LLM model without requiring extensive revisions, facilitating an incremental and economical methodology for GenAI enrichment. Ultimately, midmarket firms are considering adopting DataOps and AnalyticsOps with a strategic intent to adeptly handle the intricacies inherent in developing GenAI solutions. By prioritizing data integrity, continuous performance assessment, and progressive refinement, these firms hope to harness GenAI's capabilities cost-effectively.

Final Techaisle Take

The success of GenAI implementation probably hinges on a multi-model strategy. Firms that effectively choose, merge, and handle various models stand to fully exploit GenAI's capabilities, gaining a considerable edge over competitors. As GenAI progresses, strategies to tap into its capabilities must also advance. The key to future GenAI advancement is employing various models and orchestrating them to foster innovation and success.