Insights

Steve Daly, Senior Vice President Solutions, Global Digital Transformation

Steve Daly is the Senior Vice President of Solutions, Global Digital Transformation at New Era Technology, and specializes in cloud-native development and application modernization. He brings more than 30 years of experience providing IT solutions to start-ups, local, state, and Federal governments, Midmarket as well as Fortune 500 companies and organizations.

Microsoft Copilot Chat: The Latest Innovations Transforming the Workplace

Jul 1, 2025

This year has seen Microsoft supercharge its Copilot vision with a wave of new AI capabilities aimed at empowering employees and developers alike. From a revamped Copilot Chat experience that acts as the hub of an “agentic” workplace to specialized reasoning agents like Researcher and Analyst, Microsoft is reshaping how work gets done. As a leading solutions provider, New Era Technology is at the forefront of implementing and customizing these innovations for clients. In this article, we’ll break down Microsoft’s latest Copilot Chat announcements and analyze their strategic impact on businesses, while highlighting how New Era Technology can help organizations harness these tools for competitive advantage. Copilot Chat: The Hub of the New Agentic Workplace Microsoft’s vision for the future workplace centers around Copilot Chat as the command center for AI agents and collaborative intelligence. In Microsoft’s words, “the center of the new agentic workplace is Copilot Chat,” which lives inside the Microsoft 365 Copilot app. This unified chat interface is where employees interact with AI Copilots and specialized agents, effectively directing their new digital team members. Users can pin their most-used agents and even create custom agents for specific tasks, giving every employee a single access point to on-demand expertise and automation. Watch Steve Daly, talk about these updates in our most recent LinkedIn Live > In practical terms, the new Copilot Chat experience means employees, from frontline technicians to knowledge workers, can ask natural-language questions, delegate tasks, and orchestrate complex workflows all from a familiar chat interface. Rather than hopping between apps or manually coordinating multiple tools, workers converse with Copilot Chat to get things done. This hub integrates tightly with everyday Microsoft 365 apps (Teams, Outlook, Word, Excel, etc.), bringing AI assistance into the flow of work. Microsoft’s Work Trend Index research indicates that leading “Frontier” firms structured around AI and agents report higher productivity and more meaningful work. With Copilot Chat as the connective tissue between people and AI, organizations can move toward this agentic workplace model – one where human–AI collaboration is seamless and ubiquitous. Crucially, Copilot Chat now also includes the Agent Store, making it easy for users to discover and leverage a variety of AI agents (more on this below). By centralizing chat-based assistance and agent access, Copilot Chat lowers the barrier for employees to benefit from AI in their day-to-day jobs. This helps democratize AI across the workforce, ensuring that every employee can have a Copilot (as Microsoft ambitiously puts it, “empower every employee with a Copilot”). In essence, Copilot Chat has evolved into the “single pane of glass” for the AI-powered workplace, where humans direct AI agents to amplify productivity, insight, and automation. First-of-Their-Kind Reasoning Agents: Researcher and Analyst Among the most groundbreaking additions to Microsoft 365 Copilot in 2025 are two new built-in “reasoning agents” named Researcher and Analyst. Unveiled in March 2025, these agents are described as “first-of-their-kind” AI specialists designed to deliver secure, high-skilled expertise on demand by leveraging both your organization’s internal data and external knowledge. Researcher is an AI agent that approaches tasks the way a market analyst or strategist might. It helps users tackle complex, multi-step research projects with higher quality and accuracy than previously possible. Researcher combines OpenAI’s advanced “deep research” model with Microsoft 365 Copilot’s orchestration and search capabilities. In practice, you can ask Researcher to, for example, develop a detailed go-to-market strategy for a new product or identify emerging market trends for a quarterly business review. It will securely sift through your work data (emails, meetings, files, SharePoint) and perform web research to synthesize insights into comprehensive reports. Researcher can even draw on third-party enterprise data via Copilot connectors (formerly Graph connectors) – pulling in information from systems like Salesforce, ServiceNow or Confluence – to enrich its analysis. By simulating how a diligent strategist would gather intel and summarize findings, Researcher delivers on-demand business intelligence tailored to your context. Analyst is a reasoning agent that “thinks like a skilled data scientist,” turning raw data into actionable insights. Built on a specialized OpenAI o3-mini model and optimized for workplace analytics, Analyst excels at complex data analysis tasks. It uses chain-of-thought reasoning to break down problems and iterate toward solutions, and it can even execute Python code to analyze data, with full transparency into the code it’s running. For instance, you might ask Analyst to analyze sales data across multiple spreadsheets and forecast demand for next quarter, or visualize customer purchase patterns from a dataset. The agent will autonomously write and run the necessary code or formulas, refine its approach as needed, and produce charts, summaries, or projections – all in minutes instead of days. Because it can handle multistep computations and even do things like generate regression analyses or pivot tables via natural language prompts, Analyst brings data-science caliber insights to any user without requiring expert skills. As Microsoft put it, Analyst provides “a high-quality answer that mirrors human analytical thinking,” automating the heavy lifting of data crunching while you supervise the process. Both Researcher and Analyst maintain enterprise-grade security and compliance, accessing data within the user’s permissions and respecting policies (through the Copilot Control System). Initially rolled out through a early access “Frontier” program in April 2025, these agents became generally available to Microsoft 365 Copilot licensed customers shortly thereafter. Together, they signal a new era of AI reasoning at work – where employees at any level can instantly tap specialized AI “brainpower” for research, analysis, and problem-solving. Instead of just getting formula completions or autopilot assistance, users now have AI colleagues that can truly think through business challenges in depth. Strategically, this augments knowledge workers’ capabilities, enabling more data-driven decisions and freeing time from tedious research or analytics tasks. Every employee can have a virtual research assistant and data analyst at their side, raising the quality and speed of insights across the organization. The Copilot Agent Store: Prebuilt and Custom AI Agents at Your Fingertips To fully harness the power of AI agents, Microsoft introduced the Copilot Agent Store – a curated marketplace of prebuilt and custom agents – as part of the spring 2025 Copilot wave. Announced at Build 2025 and now generally available, the Agent Store provides a centralized way to discover, deploy, and monetize AI agents within the Microsoft 365 Copilot ecosystem. It lives directly within Copilot Chat (accessible via the left navigation), reinforcing Copilot Chat’s role as the hub for all agent interactions. The Agent Store experience is akin to an app store for AI workplace agents. Users can easily browse prebuilt agents developed by Microsoft – such as the new Researcher agent mentioned above, or domain-specific assistants for sales, marketing, finance, and more. In addition, the store features agents built by trusted partners and software vendors, as well as your own organization’s custom agents that developers or “makers” have published internally. This means an employee can find an agent for many common needs without having to build anything – whether it’s an HR help bot, a project management assistant, or a creative brainstorming coach. The store currently hosts 70+ agents (and growing) covering use cases from knowledge retrieval to complex multi-step orchestration. And it’s not just about finding new tools – the Agent Store also serves as the quick access point for agents you’ve already pinned or frequently use, so you can launch them on demand in Copilot Chat. Notably, two prebuilt agents highlighted by Microsoft – scheduled for general availability in June 2025 – are the Employee Self-Service agent and the Skills agent. These exemplify the kind of high-value solutions available out-of-the-box: Employee Self-Service Agent – Focused on HR and IT support, this agent helps employees get answers and take actions on common workplace requests, all through chat. It can retrieve company policies, benefits information, help users file support tickets or request equipment, and even perform IT diagnostics – all in one place. By connecting to organization-specific knowledge (SharePoint, internal FAQs) and systems like Workday or ServiceNow via built-in connectors, the self-service agent reduces the need to search across multiple portals or contact help desks for routine questions. Microsoft’s internal deployment of this agent saw a significant payoff: employees became 25% more likely to get accurate HR answers and 49% less likely to open support tickets compared to earlier tools. This translates to faster resolutions for staff and lower support burden for IT/HR teams. The Employee Self-Service agent is included with Microsoft 365 Copilot and can also be used on a pay-per-message basis in Copilot Chat, making it easy for organizations to adopt. Skills Agent – This agent addresses the challenge of mapping and utilizing talent within large organizations. Powered by a new People Skills data layer in Microsoft 365, the Skills agent helps users find colleagues with specific expertise, understand the skill profile of teams, and even allows employees to update their own skill tags. For leaders, it offers an up-to-date view of organizational strengths and skill gaps, supporting strategic workforce planning and project staffing. Imagine being able to quickly query, “Who in our company has experience with Azure AI deployments?” and having the agent produce a list of experts and their relevant project history. By centralizing skill data and making it queryable, the Skills agent enables knowledge sharing and makes it far easier to assemble the right teams. It will be generally available to Copilot licensees, putting advanced talent analytics at managers’ fingertips. The Agent Store doesn’t just empower end users – it also creates a new channel for developers and software providers. Partners can build niche or industry-specific agents and publish them to the store for enterprise customers to discover. Microsoft notes that the store “enables software companies to monetize their agents” by surfacing them directly in the M365 apps where users work. For example, a third-party vendor might offer a supply chain agent or a legal contract analysis agent via the store. This opens a rich ecosystem where organizations can benefit from community innovations without having to develop every solution in-house. As a Microsoft Solutions Partner, New Era Technology has been an early adopter in this space, developing custom Copilot agents for clients. Our team has worked on scenarios ranging from smart onboarding bots for HR to industry-specific analytics agents, leveraging Microsoft’s Copilot Studio. By publishing curated agents, New Era helps clients jumpstart their AI journey with pre-built solutions that address common needs. And because these agents can be further customized, we ensure they fit each client’s unique processes. In essence, the Agent Store allows New Era to deliver our expertise at scale, and our clients to deploy trusted AI assistants quickly and securely.

Copilot in Microsoft 365: Bringing Generative-AI into the Modern Workplace

Feb 10, 2025

Artificial Intelligence (AI) has been a game changer throughout its evolutionary track over the past years. The utility lies in its inherent ability to simplify things, help technology be more accessible even to novice end-users, and ultimately lead to the democratization of application usage that the barriers of complex technical skills had hitherto confined. As a part of our series of blogs on Microsoft Copilot, and how it has revolutionized the use of generative-AI, we bring across an introduction to the Copilot in the various Apps of the Microsoft 365 suite. Stay tuned, as the change has been overwhelming all across its journey right to your workplace! Copilot saves time, increases efficiency and productivity with data accuracy and relevancy of information, redefines how the modern workplace functions across its routine tasks, and aligns with the organization’s security, privacy, and compliance policies set in Microsoft 365. As we explore its vast set of features, we also focus on essential aspects influencing its usage-Data security and accuracy. Read ahead to know more! To summarize Copilot’s evolution, here’s what Satya Nadella, CEO of Microsoft Technologies, had to say about it. “Today marks the next major step in the evolution of how we interact with computing, which will fundamentally change the way we work and unlock a new wave of productivity growth.”...“With our new Copilot for work, we’re giving people more agency and making technology more accessible through the most universal interface — natural language.” How does it Work? Copilot lies on the foundation of Large Language Models (LLM) for creating and parsing text in natural language. The Copilot Engine is an advanced processing and orchestration tool system that assesses the context of the user input with Microsoft Graph-an API that connects various M365 Apps, emails, chats, calendars, and the available data in them and sends it to the LLM. The received response is again contextually processed and analyzed for security, compliance, and privacy reviews before being sent to the Microsoft 365 App to generate the relevant output to the user’s query. In addition, Copilot for Microsoft 365 comes with a feature called Business Chat, an interactive natural language Chatbot integrated with Microsoft Teams. Business Chat can search across files of various types, such as presentations, spreadsheets, emails, and Word documents. It generates the required output, such as the status of a project, by aggregating all the relevant information across related files and summarizes the output with links to individual items. Copilot also includes a feature called Semantic Index, which is essential to its deployment. This feature creates a conceptual map of all the information and users across the business. It enhances searching by not just limiting it to the relevant terms but including other advanced attributes such as the usual format used for such documents, the time, and the user(s) that they are usually created or used by, amongst others. The map creates a huge stored set of vectors- mathematical representations of features and attributes of business information. Semantic Index only accesses the information the user has permission to access during searching based on the user prompt. Let’s look at Copilot’s vast features across various commonly used Microsoft 365 Apps. It turns user input in a natural language into stunning visualizations, informative presentations, contextually relevant documents, meeting notes, action items, and more. How Copilot Transforms Upskilling > Copilot in Various Microsoft 365 Applications Word: With Copilot in Microsoft Word, users can create a first draft of the document they want to make, generate improvements, edit, and rewrite text to enrich tone, tenor, and information. It can also summarize existing documents regarding existing information in the organizations. Such generative AI helps reduce the time taken for drafting documents such as proposals and the time for research and referencing, paving the way for increased efficiency and accuracy. PowerPoint: Copilot in PowerPoint helps users create new presentations from Word documents, spreadsheets, and user guidelines. Style, alignment, speaker notes, animation, and images get automatically generated with relevance to the information. It supports the alteration of existing presentations. Outlook: Copilot in Outlook helps you outline the key points and questions across multiple persons in an email thread. You can automatically compose individual and group responses, edit and summarize them, adjust the length and tone, and have action items flagged. These features make communication faster, effective, and more productive in a modern workplace. Excel: Copilot redefines the conventional way of using Excel. From automatically creating graphs and visualizations to finding data and correlations to developing and analyzing what-if scenarios and data models, users can use a natural language prompt to leverage the extensive depth of features that Excel provides to users with in-depth technical knowledge. Teams: Teams has consistently been the most widely used remote communication tool, and Copilot accentuates its vast capabilities. You can automatically organize discussion points, key actions for individual users, and query in the chat on what you have missed, all without disturbing the flow of the meeting or even after that. Advanced features include: Automatic creation of meeting agendas based on the existing chat history Debriefing late attendees Scheduling follow-up meetings and identifying the right contacts, along with real-time translation in more than 100 languages In addition, Copilot has also been introduced for Microsoft Dynamics ERP and CRM, making way for driving generative AI into enterprise management. Data Security and Accuracy in Microsoft 365 Copilot Data security is a major concern for enterprises using Copilot with Microsoft 365, as the core business data is what gets accessed. Microsoft addresses this aspect with various features such as two-factor authentication, M365 Isolation controls, permission-based access for individual users to have at least view privileges for the data they are requesting, along with a feature to configure access only to information on the user’s tenant, and not other tenants that they are a part of (Such as with B2B guest access). These safety measures prevent data leakage into user groups. Copilot ensures the confidentiality of individual information that is of primary importance in a workspace in a secure, compliant, and regulated manner and guarded by Microsoft’s enterprise-grade security policies. It adheres to various compliance requirements such as the European Union (EU) Data Boundary and GDPR (General Data Protection Regulations). Furthermore, in regards to data accuracy, Copilot is backed by constant innovation and best practice implementation of guardrails, content filters, and blocking of sensitive data with Microsoft’s Azure OpenAI service. It uses advanced Microsoft technologies such as InterpretML and Fairlearn to detect and rectify data bias. Business data is not used to train other LLMs, is integral to the specific business, and is not available to access by ChatGPT. Licensing and Extensibility The licensing of Copilot for Microsoft 365 will be available from November 1’, 2023, along with Microsoft 365 chat. Copilot for Microsoft 365 has an extensibility model for plugins, making integration of third-party services possible across the business. Currently, it has three types of plugins- ChatGPT plugins, Power Platform connectors, and Teams message extension plugins. The above features of Copilot for Microsoft 365 save time, increase efficiency and productivity with data accuracy and relevancy of information. It redefines how the modern workplace functions across its routine tasks and aligns with the organization’s security, privacy, and compliance policies. Copilot for Microsoft 365 is truly a game-changer in generative-AI, and drives simplified usage, even for novice users. For information on how you can enhance your business productivity with Copilot in Microsoft 365, contact us, and we will be glad to help. New Era Technology is a Microsoft Solutions Partner, with vast experience in custom solutions using Microsoft technologies across various industry verticals.

AI Code Assistants: Revolutionizing Development with GitHub Copilot

Nov 12, 2024

Introduction to AI Code Assistants In the dynamic world of software development, AI code assistants have emerged as transformative tools that change how developers write and manage code. Traditionally, programmers depended on their skills and various resources—like documentation and libraries—to produce software efficiently. However, AI-driven solutions like GitHub Copilot now offer real-time coding suggestions powered by machine learning algorithms, streamlining tasks such as writing repetitive code and debugging. These AI assistants not only enhance productivity but also serve as valuable resources for learning. They guide developers through unfamiliar languages and frameworks, making them especially beneficial for those new to the field. By automating routine tasks, these tools allow developers to focus on more complex problems and creative aspects of software engineering. As the need for rapid software delivery grows, AI code assistants are becoming essential in development teams. They foster collaboration and knowledge sharing, promoting consistency and quality in coding practices. Understanding how to utilize these tools effectively is crucial for developers at all levels of experience. Understanding GitHub Copilot GitHub Copilot, a product of the collaboration between GitHub and OpenAI, is a standout AI code assistant. It seamlessly integrates into popular integrated development environments (IDEs) and uses machine learning to analyze context and generate real-time code suggestions. This unique combination of features makes it an invaluable asset for developers across various programming languages and frameworks. Watch our GitHub Copilot Demo > How GitHub Copilot Works GitHub Copilot employs a sophisticated language model trained on vast amounts of publicly available code. As developers type, the AI analyzes the context, including variable names, function signatures, and surrounding code, to generate relevant suggestions. These suggestions can range from simple line completions to entire function implementations, significantly speeding up the coding process. Key Features of GitHub Copilot Intelligent Code Completion: Offers context-aware code suggestions as you type. Multi-language Support: Works with numerous programming languages and frameworks. Whole Function Generation: Can suggest complete function implementations based on comments or function names. IDE Integration: Seamlessly integrates with popular IDEs like Visual Studio Code, Visual Studio, and JetBrains IDEs. Customization: Allows developers to accept, modify, or reject suggestions, maintaining complete control over the code. Benefits of Using GitHub Copilot Increased Productivity By automating repetitive coding tasks and providing intelligent suggestions, GitHub Copilot significantly reduces developers' time on boilerplate code. As a result, they can concentrate on more complex problem-solving and the creative aspects of software development. Faster Learning Curve GitHub Copilot is not just a tool, but an interactive learning companion for developers learning new languages or frameworks. It provides examples and implementations to help developers better understand best practices and coding patterns, enhancing their knowledge and skills. Reduced Context Switching With its ability to generate code based on natural language comments, GitHub Copilot minimizes the need for developers to switch between documentation and their IDE, maintaining focus and improving workflow efficiency. Enhanced Code Quality While not a substitute for thorough code review, GitHub Copilot can help maintain consistent coding styles and suggest optimized implementations, potentially improving overall code quality and boosting developers' confidence in their work. Challenges and Considerations Ethical and Legal Concerns Using AI-generated code raises questions about intellectual property rights and the potential for reproducing copyrighted code. GitHub has implemented measures to address these concerns, but users should remain aware of the implications. Over-reliance on AI Suggestions Developers must balance leveraging AI assistance and maintaining their critical thinking and problem-solving skills. Over-reliance on AI-generated code could hinder long-term skill development. Code Security and Privacy While GitHub Copilot is designed with security in mind, developers should always review generated code for potential vulnerabilities and ensure it meets their project's security standards. The Future of AI Code Assistants As AI technology advances, we can expect AI code assistants like GitHub Copilot to become even more sophisticated. Future developments may include: Improved context understanding and more accurate suggestions Enhanced support for domain-specific languages and frameworks Integration with other development tools for a more comprehensive coding experience Advanced code refactoring and optimization capabilities Conclusion GitHub Copilot and other AI code assistants represent a significant leap forward in software development tools. By augmenting human creativity with machine intelligence, these tools have the potential to dramatically increase coding efficiency and help developers tackle complex challenges more effectively. As the technology evolves, it will be crucial for developers to adapt their workflows and leverage these AI assistants responsibly to maximize their benefits while maintaining high code quality and security standards. How Microsoft Copilot Transforms Upskilling >

Empowering Employees in the Digital Age: How Microsoft Copilot Transforms Upskilling

May 15, 2024

In the digital transformation era, organizational initiatives' success often depends on employees' ability to adapt and excel amidst continual change. Microsoft Copilot is at the forefront of revolutionizing employee upskilling, ensuring that workforce capabilities align seamlessly with evolving technological demands. What is Microsoft Copilot? Launched in 2023, Microsoft Copilot is a productivity platform powered by generative artificial intelligence (GenAI) that Microsoft has dubbed "your everyday AI companion." It leverages large language models (LLMs) combined with an organization's data to help streamline routine tasks, automate workflows, and boost collaboration. It also integrates with Microsoft 365 apps to turn user input into stunning visualizations, presentations, documents, meeting notes, action items, and more. The platform sets itself apart with its user-friendly interface and interactive tutorials, making the mastery of new technologies and processes a breeze. Microsoft Copilot simplifies complex concepts into manageable modules, allowing employees to learn at their own pace. This approach not only reduces the learning curve but also facilitates a seamless transition into digital-centric operations. Microsoft Copilot's functionality goes beyond its user-friendly design; it provides real-time assistance and context-sensitive prompts, offering employees immediate support. This feature is particularly beneficial in a fast-paced business environment, where maintaining productivity is of utmost importance. Microsoft Copilot adds value with personalized learning recommendations and adaptive algorithms that tailor training content. This personalized approach ensures that learning is relevant and time-efficient, allowing employees to focus on acquiring skills specific to their roles and responsibilities. The benefits of Microsoft Copilot are not just theoretical; they are quantifiable. The platform tracks technology adoption rates, the time employees take to achieve proficiency with new tools, and the overall impact on productivity and operational efficiency. These data points are invaluable for organizations to assess Microsoft Copilot's effectiveness and refine their upskilling strategies accordingly. Investing in Microsoft Copilot also demonstrates a firm's commitment to its workforce, signaling to employees that they are valued and supported. This commitment fosters a corporate culture characterized by continuous learning, adaptability, and innovation—essential for staying competitive in a rapidly changing business landscape. Microsoft Copilot for Microsoft 365 Microsoft Copilot for Microsoft 365 is a game-changer for organizations using the Microsoft ecosystem. This AI-powered assistant seamlessly integrates with Microsoft 365 apps like Word, Excel, PowerPoint, and Outlook, empowering employees to work more efficiently and effectively. With Microsoft 365 Copilot, employees can: Generate professional emails, reports, and presentations with AI-assisted writing suggestions. Analyze data in Excel using natural language queries, making data insights accessible to non-technical users. Automate repetitive tasks, such as data entry and formatting, freeing up time for higher-value work. Receive real-time guidance and support while working within Microsoft applications, reducing the need for extensive training. By leveraging Microsoft Copilot for Microsoft 365, organizations can significantly enhance employee productivity, collaboration, and overall digital proficiency. Microsoft Copilot for Security Microsoft Copilot for Security is a powerful tool that helps organizations strengthen their cybersecurity posture by upskilling employees in security best practices and threat awareness. Key features include: Personalized security training tailored to each employee's role and level of technical expertise. Simulated phishing attacks and other real-world scenarios to test and reinforce security knowledge. Real-time security alerts and guidance when employees encounter potentially malicious content or engage in risky online behavior. Gamified learning experiences that make security training engaging and memorable. With Microsoft Copilot for Security, organizations can cultivate a strong security culture, reducing the risk of human error and bolstering their overall cybersecurity defenses. Microsoft Copilot for Sales Microsoft Copilot for Sales is a transformative solution that empowers sales teams to excel in the digital age. By leveraging AI and machine learning, Microsoft Copilot for Sales provides salespeople with the insights, guidance, and automation they need to close more deals and drive revenue growth. Key benefits include: AI-powered lead prioritization and opportunity insights, enabling salespeople to focus on the most promising prospects. Automated data entry and CRM updates, freeing up time for more strategic selling activities. Real-time coaching and guidance during sales calls, helping salespeople navigate complex conversations and objections. Personalized learning paths that upskill salespeople in areas like social selling, virtual presentations, and consultative selling techniques. By investing in Microsoft Copilot for Sales, organizations can accelerate their sales cycles, improve win rates, and drive sustainable revenue growth in the digital era. Your Ally in Digital Transformation As organizations face the accelerating pace of business evolution, the significance of systematic employee upskilling cannot be overstated. With Microsoft Copilot, companies have a reliable ally to help navigate the complexities of digital transformation, ensuring that their employees are well-equipped with the necessary skills and support. Ultimately, the efficacy of digital transformation initiatives heavily relies on the people involved. By leveraging platforms like Microsoft Copilot, organizations invest in their technological infrastructure and the human potential that propels their success. This dual investment enhances immediate business outcomes and long-term organizational resilience, creating a compelling value proposition that is hard to overlook. New Era Technology is uniquely positioned to help organizations discover and execute their AI strategies, including the implementation of Microsoft Copilot across various business functions. With deep expertise in digital transformation and a proven track record of success, New Era Technology can guide companies through the process of identifying AI use cases, selecting the right tools and platforms, and driving adoption and change management. By partnering with New Era Technology, organizations can unlock the full potential of AI and Microsoft Copilot, accelerating their digital transformation journeys and empowering their employees to thrive in the digital age. Ready to learn more? Contact us today — we're here to help.

Finding the Right Tools to Support Your AI Adoption Strategy

Jan 22, 2024

In an era quickly shaped by the advancements of generative artificial intelligence (GenAI), the responsibilities of Chief Information Officers (CIOs) and Chief Technology Officers (CTOs) have shifted. They must understand the potential of GenAI and guide their organizations in capitalizing on this transformative technology. Understanding the crucial importance of tooling in implementing GenAI, CIOs and CTOs must focus on choosing tools that match the advanced nature of this technology and assist in its effective utilization. This strategic approach to tooling is fundamental in speeding up innovation, delivering superior quality, and fostering a competitive edge in a GenAI-driven market. "Technology is nothing. What's important is that you have a faith in people, that they're basically good and smart, and if you give them tools, they'll do wonderful things with them." ~ Steve Jobs The choice of GenAI tools morphs from purely a technical decision to a strategic one with implications for the business's reputation, customer trust, and overall success in this digital era. Viewing it from this perspective, the challenges posed by tooling in adopting GenAI become central to not just tech strategy but the entire organizational direction. Factors That Can Help (or Hinder) Your AI Adoption Strategy Here are some of the ways that the lack of suitable tools can significantly hinder your AI adoption strategy: Innovation and Development Good tools are essential for developers and researchers to experiment, iterate, and enhance GenAI models. Limited or poor-quality tools can slow the innovation cycle, making it challenging to advance GenAI technology efficiently. Quality and Reliability Poorly designed tools may produce subpar results, leading to a lack of trust in GenAI's outputs. This can affect the perception of the technology's reliability and accuracy, deterring its adoption in critical fields where precision is paramount. Integration and Compatibility The need for robust tools can make integrating GenAI into existing workflows and systems challenging. This could be a significant barrier for organizations looking to adopt GenAI solutions but find the integration process needs to be more convenient and compatible with their current infrastructure. Accessibility and User Experience Without intuitive and user-friendly tools, potential users, especially those who are not tech-savvy, may find it difficult to interact with GenAI systems. User experience could lead to a lower adoption rate as the technology would seem inaccessible or too complex to a broader audience. Education and Training Good tools often come with educational resources, documentation, and community support, crucial for learning and adopting new technologies. The learning curve becomes steeper in their absence, and potential users might need more guidance to use GenAI effectively. Ethical and Responsible Use Beyond the technical aspects, leaders face the critical challenge of ensuring responsible and ethical adoption of GenAI technologies. With GenAI becoming an integral part of business processes, the burden of aligning their deployment with the organization's values and ethical norms is ever-growing. Tools designed with ethical considerations and responsible GenAI principles in mind are crucial for the safe adoption of it. Lack of such tools can lead to unethical use or unintended harmful consequences, tarnishing the reputation of GenAI technology. A Strategic Approach to GenAI Tooling In conclusion, you must recognize the instrumental role of tooling in successfully integrating and adopting GenAI. The responsibilities of CIOs and CTOs extend beyond the technical aspects, pushing them to facilitate the choice of the right tools that meet the technical requirements of GenAI and align with their organizations' ethical norms and values. Tools offer a gateway to accessibility, innovation, quality assurance, seamless integration, education, and ethical use of GenAI. A strategic approach to tooling defines the path for organizations to harness the true potential of GenAI, laying a solid foundation for the accelerated innovation, heightened quality, and competitive edge that this technology promises. Therefore, the choice of tools becomes a vital determinant of the tech strategy and overall organizational direction in this digital era. References https://www.rollingstone.com/culture/culture-news/steve-jobs-in-1994-the-rolling-stone-interview-231132/

Looking for ROI in all the wrong places: How to get your cloud value back on track

Jul 15, 2022

A version of this article was originally published in Forbes. Theoretically, a case could be made for running your workloads, data, and applications entirely from on-prem servers. But realistically? That use case is vanishingly small. Nearly all companies can benefit from the cloud. And most organizations are well aware of the benefits cloud modernization confers. You’ve heard the touts: Cloud migration leads to faster run times, greater efficiency, and — here are the magic words — significant cost savings. As with any major business move, return on investment drives a substantial number of cloud decisions. But when you make those calls without a strategy specifically tailored to cloud environments, the risks add up. You wouldn’t relocate your corporate headquarters without significant strategic reasoning. Relocating your technical real estate ought to trigger the same level of analysis and corporate soul searching. If you aren’t seeing the ROI you expected from your cloud investment, you may need to consider a more strategic approach. Why you’re not seeing cloud ROI…and what you can do about it Companies have technology problems: aging servers, feral architectures, legacy applications, redundant workloads, wild west dev shops…the list goes on. Faced with a mess on the premises and a cloud mandate from leadership, it’s easy to understand why one of the most common strategies for cloud migration is lift-and-shift. All too often, though, a one-for-one move to the cloud is used as a shortcut to avoid having to create a full-blown cloud strategy and roadmap. Here’s how to avoid common ROI pitfalls. ROI pitfall: Unexpected costs Moving to the cloud can be a significant cost-saving strategy for your information technology budget, but it can also have the opposite effect. Without taking the time up-front to tune workloads and assess usage, you could wind up paying more for cloud storage/use than you used to spend for an on-prem solution. Understanding cloud pricing models, including getting clarity on all the variables that affect pricing in the cloud, couldn’t be more important — it isn’t an apples-to-apples comparison to on-prem. Cloud costs are directly related to resources consumed, so lifting and shifting without a strong strategic foundation can cannibalize your savings. To save more in the cloud environment, consider: Resizing: Do all of your workloads run at capacity all the time? Or are they often over-provisioned? Would a lower consumption rate with surge capacity work better for your needs? Retiring: Are any of your applications or workloads redundant? Lift-and-shift migrations can shed light on previously siloed tasks that could be streamlined to reduce cloud consumption. Replacing: Would a different solution make more sense? A cloud migration offers the opportunity to rethink your legacy applications and combine or replace some of your workloads and applications. ROI pitfall: Ungoverned actions Your teams may be used to a high degree of autonomy, with different business units responsible for their own tech and data usage. Once you move to the cloud, however, that shadow IT culture can cost you. If users deploy new resources and enable additional capabilities to the cloud at their usual rate, your spending can escalate quickly. To avoid painful consumption spending, here’s how a fresh look at policies and procedures can help: Rethinking: This is a good time to standardize processes around development, quality, testing and change management. Recommitting: A cloud environment makes governance more important for your organization than ever. Take the opportunity to recommit to strong governance standards across your organization—and be sure you have change management plans in place to support the shift. ROI pitfall: Unanticipated fluctuations Even the best cloud strategies can’t always anticipate the variability of cloud usage. Costs and efficiencies of different cloud platforms might vary month to month or even week to week. Some companies try to account for the volatility by building each of their workloads four or more different ways so they can quickly shift from one cloud provider to another. Others get fed up and go all in with one platform. Neither option is cost-effective. To make the most of cloud price fluctuations, consider new ways of working, like: Replatforming: Are your legacy systems still serving you well? Could the costs of a hardware or software upgrade be balanced out by greater efficiency or better cloud usage over time? Refactoring: One way to manage cloud environments is containerization. As I wrote in my previous Forbes article, “Once your workloads are containerized, adding automation can save you even more by establishing, testing, and refining models for workload placement without relying on time-consuming manual decisions.” Google Cloud Platform, AWS, and Azure all have forecasting tools you can use to further refine your automation models. Rehosting: Containerized workloads enable on-the-spot decisions about where to run a task. Realizing savings then becomes as easy as a drag and drop to the cheapest or most efficient cloud or on-prem location. Rearchitecting: Could developing cloud-native applications serve the same needs but in more efficient, modern, or cost-effective ways? Why you should start with the end in mind While each of these tactics has value, the best way to avoid surprises and see ROI for your cloud investment faster is to start with a strategy. A cloud mandate without a cloud strategy is a recipe for cloud disappointment Up-front strategic planning can save you significant rework and help you avoid costly mistakes with your cloud migration. To maximize your cloud ROI, key topics to include in your strategy are: Evaluating your current architecture, technology, or processes: What’s working and what could be improved? Identifying redundancy and opportunities for improvement: What could be streamlined in your code, workloads, or data? Articulating fluctuations in your use patterns: How are your workloads prioritized? Could your data and storage needs be tiered? What might optimal provisioning look like for your organization? When it comes to cloud ROI, grounding your operations and tactics in strategy is non-negotiable. The more intentional your organization is about its cloud deployment, the more quickly your ROI will outpace expectations.

From workload migration to workload transformation: Five ways to get your cloud ROI back on track

May 25, 2022

A version of this article was originally published in Forbes. Remember when your business first got into the cloud, and the whole idea seemed edgy and exciting? If you’re like most organizations, some years have passed since those early days, and you may be feeling a little bogged down with workload migration. You might not be seeing the efficiencies you imagined. Your cloud ROI might even be slipping. You can’t roll back to square one, but you can get back on track. Every journey is different, but as we’ve helped companies optimize their technology, we’ve identified five key ways to elevate your workload migration into true workload transformation. Realign for impact. Workload transformation can be a long game, but it doesn’t have to be a slog. Evaluating processes and mapping out potential efficiencies can help ease transition pain points and accelerate your time to proving results. If you haven’t taken a fresh look at your cloud roadmap lately, it may be time to regroup and make sure your workload optimization strategy is still aligned with business priorities and resources. Start with your current state. You might ask questions like: What does your current workload array include? How are different environments performing? Which technical skillsets do you have in-house? Which short- and long-term business processes are impacted by technical workloads? Next, align your workload transformation vision with broader business goals. A short stakeholder workshop might allow you to uncover ideas such as: Ways your cloud strategy could help to advance your broader business goals How to prioritize your workload migration to support desired business outcomes like cost, speed, innovation, or streamlined functionality Learn more about cloud strategy workshops >> Zoom in before you zoom out. Workload migration optimizes consumption to help you run leaner. But you don’t have to stop there. True workload transformation comes from maximizing efficiencies at every step. As you consider ways to transform your workloads, it’s worth taking the time to zoom in on what those entail. If your goal is a modern architecture that allows rapid pivots and scalability, but your applications and processes need some work, you may need to start with foundational improvements before jumping into more sophisticated tools and tactics. Make sure you’re keeping an eye on the details throughout your cloud migration journey. Some factors to keep in mind include: Adopting best practices like unit testing and documentation for application development, especially as you move into microservices and connecting cloud-native apps to legacy systems. Stress-testing each application or feature prior to migration to determine if it will perform as expected in a cloud environment. Checking performance, reporting, and data egress needs before making placement decisions. Choosing the right instance type for your migration based on the workload’s required memory, connectivity, and storage to avoid performance impact. Aligning migration strategies with your security standards, including backup and business continuity requirements, access, and API requirements. Learn more about infrastructure assessments >> Ditch the hype. Contrary to what you might have heard, there’s no one-size-fits-all solution to workload transformation. With the digital landscape shifting faster and faster, getting sidetracked and stuck in the mud are all too easy. Don’t buy into the hype. Joining Team AWS or Team Azure or Team Google won’t do your business any favors in the long run. That’s why many businesses move into a multicloud or hybrid cloud model, which adopts a platform-agnostic approach to workload optimization. In this framework, you might have some workloads running on-prem, while others operate in some combination of cloud options. Learn more about cloud technology strategy >> Be open-minded. However, even with variable workloads, the costs and efficiencies of different cloud platforms might vary month to month or even week to week. Some organizations look at that and figure they can’t afford to build each workload four (or more) different ways, so they go all-in with one platform. That can be short-sighted. Instead, many companies opt for some degree of containerization. Using Kubernetes and DevOps, containerizing workloads lets businesses make on-the-spot decisions about where to run a workload. Using this method, your team can essentially drag and drop a workload to the cheapest or most efficient cloud or on-prem location. But why stop there? Once your workloads are containerized, adding automation can save you even more by establishing, testing, and refining models for workload placement without relying on time-consuming manual decisions. Learn more about modernization roadmaps >> Get there faster. Done right, workload transformation eliminates overrun. When you find the right ways to combine, host, and run your workloads, your whole business benefits from the efficiency. And you don’t just save in terms of performance and scalability — you also save time and money. Wouldn’t it be great to transform faster? Fusion helps you innovate and modernize your architecture while supporting ongoing feature development and production. True workload transformation supports your ongoing business needs while also positioning your company to win in the future. Let us know how we can help. Assess your workload strategy >>

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Steve Daly, Senior Vice President Solutions, Global Digital Transformation

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From workload migration to workload transformation: Five ways to get your cloud ROI back on track

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