Techaisle Blog

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.

Today's cybersecurity landscape is a complex maze, with a multitude of vendors contributing to a convoluted and intricate security stack. The evolution of security from traditional perimeter defenses around private data centers to a distributed network of branch offices, remote workers, and IoT devices has necessitated a radical shift in security strategies, with a focus on enforcement points across the network. At its core, security is a data challenge, where the sheer volume of data often hinders the identification of actionable insights, leading to an imbalanced signal-to-noise ratio and the prevalent issue of alert fatigue. Effective data connection across control points is crucial to transform low-level alerts into critical insights that demand immediate action.

Under the visionary leadership of Jeetu Patel, Executive Vice President and General Manager of Security and Collaboration, Cisco's security product portfolio has undergone a transformative evolution. This radical re-envisioning of security paradigms has significantly refined Cisco's security cloud solutions, streamlining the adoption process for an integrated security platform. In response to the complexities of distributed environments, Cisco introduced 'Hypershield,' a pioneering expansion of the hyper-distributed architecture concept tailored to meet the demands of hyper-distributed security. The strategic acquisition of Splunk has further fortified Cisco's capabilities, enabling it to manage the signal-to-noise ratio effectively. Leveraging Splunk's advanced data analytics, Cisco aims to mitigate alert fatigue by converting many low-level events into meaningful, actionable insights.

The Birth of the Cisco Security Cloud Platform

In June 2022, Cisco introduced the Cisco Security Cloud Platform at the RSA Conference, a visionary solution designed to streamline the complexity of managing disparate security tools. This platform offers a unified experience, ensuring secure connections for users and devices to applications and data, irrespective of location.

The platform's emphasis on openness provides a comprehensive suite for threat prevention, detection, response, and remediation at scale. At its core is a powerful firewall, enhanced with AI for superior analysis. Identity management is flawlessly integrated, allowing every Cisco security product to leverage AI-driven insights and user authentication.

Cisco addressed the challenge customers faced with the vast array of security products—approximately 30 products with over 1,000 variations—by significantly simplifying its portfolio. Customers now have a choice of three intuitive suites: User Protection, Cloud Protection, and Breach Protection. These suites are not merely bundled; they are fully integrated, facilitating seamless communication and improved functionality, making security management far more straightforward and efficient.

Tackling Hyper-Distributed Security with Cisco Hypershield

As an industry analyst, I am convinced that Cisco's recent strides in security innovation are nothing short of impressive. The 2023 launch of Cisco Multi-cloud Defense, Cisco XDR, Cisco Secure Access, and advanced firewall functionalities marked a year of significant progress. The introduction of Cisco AI Assistant was a testament to its commitment to continuous innovation. In 2024, Cisco took a giant leap by introducing Hypershield, a sophisticated, AI-enhanced, cloud-native security system set to redefine cybersecurity.

The rapid pace of AI innovation, coupled with the complexity of implementation, creates challenges for many businesses. Concerns around data security, intellectual property, and the high costs of running and managing AI models further complicate their AI journey. This is where Dell steps in, leveraging its extensive expertise in AI and innovative solutions to help businesses navigate these challenges. The company focuses on developing data management solutions, launching powerful computing hardware, and building partnerships to ensure businesses are equipped for the demands and opportunities of AI.

As part of its commitment to democratizing AI, Dell unveiled the Dell AI Factory at the recent Dell Technologies World (DTW) conference in May 2024. This unique initiative stands out for providing customers access to one of the industry's most comprehensive AI portfolio, from device to data center to cloud. The AI Factory, a distinctive combination of Dell's infrastructure, expanding partner ecosystem, and professional services, offers a simple, secure, and scalable approach to AI delivery. Its objective is to integrate AI capabilities directly within data sources, transforming raw data into actionable intelligence and thereby enhancing business operations and decision-making processes. In addition, Dell announced new channel programs to foster collaboration and accelerate AI adoption, recognizing the vital role of channel partners in driving revenue. With Dell's AI Factory, businesses can confidently embark on their AI journey, knowing they have a trusted partner to guide them every step of the way.

Understanding the AI Factory

To adopt AI on a large scale, a robust infrastructure is crucial. Conventional IT setups designed for regular computing often struggle to meet the complex demands of AI workloads. This is where the concept of an AI Factory becomes significant. Picture it as a specialized center with powerful computing systems, advanced data processing tools, and a team of AI experts. The AI Factory is designed to streamline AI solutions' development, deployment, and scaling, making it easier and faster. By consolidating these elements, an AI Factory ensures that AI innovations can be swiftly created and applied, reducing delays and increasing efficiency, thereby simplifying the complex process of AI deployment for businesses. With Dell's AI Factory, businesses can feel relieved of the implementation challenges, knowing they have a trusted partner to guide them every step of the way.

The Dell AI Factory simplifies AI deployment by offering essential components like servers, storage, and networking in one place. This streamlined approach eliminates the need for businesses to find and combine these components separately – and ensures they work well together, saving significant time and resources. Customers also gain access to Dell's AI expertise and a reliable ecosystem of partners. This comprehensive solution empowers businesses to choose from individual products or create custom configurations to fit their AI needs. The Dell AI Factory also offers different consumption models, including purchases, subscriptions, and as-a-service options, providing businesses the flexibility to adopt AI at their own pace. With Dell's comprehensive AI portfolio, businesses can feel secure knowing they have all the tools they need for successful AI adoption.

The Dell AI Factory is not just a collection of products. It is a comprehensive solution designed to simplify AI integration for businesses of all sizes.  Whether a business, like SMBs, is starting small with PCs or deploying AI across a server network, the Dell AI Factory equips the customers with the tools and expertise to achieve real-world results.

This powerful combination of high-performance infrastructure, industry-leading services, and deep AI knowledge can empower businesses to embrace AI confidently.  The Dell AI Factory goes beyond just hardware, offering a complete package that simplifies the entire AI adoption process, making Dell a key player in accelerating real-world AI applications. 

Dell AI Factory Infrastructure

Training and deploying AI models require significant computational power and vast datasets. While convenient for many businesses, public cloud solutions can become expensive for these resource-intensive tasks and introduce security risks and the potential for IP infringement. Businesses increasingly seek on-premises solutions for greater control over data and resources and cost optimization. The Dell AI Factory addresses these challenges by providing a robust foundation built on Dell's core strengths in infrastructure solutions—servers, storage, data protection, and networking. This robust infrastructure delivers the necessary computational muscle and storage capacity for AI workloads.