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  1. “Copilot is so much more than a new feature within Microsoft 365. It’s about transforming the way people work.”

    Whether it’s drafting a job description, sorting help desk tickets or visualizing complex data in seconds, Copilot is already creating huge value in the hands of millions of workers. 

    A study from the Boston Consulting Group found AI-assisted workers were 25% faster. They produced 40% better quality work. And they took on 12% more tasks than a comparable group without AI assistance.

    Notably, this study used open generative AI platforms, suggesting the real impact of AI tools fully integrated with proprietary data and applications could be much higher.

    It’s hard to ignore the implications for competitiveness, both on the organizational and in one’s personal career. The age of AI is here, like it or not.

    Charting your “flight path” to Copilot adoption

    To tap into all this potential, we recently expanded our 30-year partnership with Microsoft to better help our customers get the best value from this investment.

    Taking your most important asset – proprietary data on your customers, products and markets – and having that generate truly game-changing outputs for your business takes a lot of planning and data integration capability. This needs to happen without losing sight of security and governance.

    To get it right “customers should not be looking at AI or Copilot for Microsoft 365 as a simple transaction or a services project,” says Chris Woodin, Sr. Vice President – Solutions and Alliances at Softchoice.

    Instead, they need to see Copilot adoption in terms of a long-term journey. That journey has multiple stages that form what we call the “flight path” for Copilot adoption. Here’s how it works.

    Step 1: Plan your business case for Copilot

    The first stage of the flight path is to define the vision, goals, and success criteria for using Copilot for Microsoft 365 in your organization.

    We call this the “Plan” phase. Here, we look at the universe of potential use cases that might create meaningful change in value for the business and justify the case for change.

    For example, you may want to use Copilot to improve the productivity and quality of your content creation, marketing, sales, or customer service teams. You might consider deploying it to IT to improve service desk ticketing, security alerts or any number of other applications. How Copilot shows up will depend on the context in which you operate today and where AI can make a difference in real productivity terms.

    To help, we can support as you plan, build and win support for your business case, create a roadmap and align those with a stake in decision-making on the scope and timeline of the project.

    Getting Clear on Copilot Adoption – The Business Case

    Step 2: Assess your technical and organizational readiness

    The next stage is to evaluate the current state of your IT environment, licensing, security posture, and organizational readiness for Copilot for Microsoft 365.

    This is the “Assess” phase. In this phase, you need to make sure that existing applications, business processes, and data can be integrated effectively into Copilot. This involves a gap analysis to identify any risks, issues, or dependencies that are going to need remediation before you deploy.

    For example, you may need to upgrade your Microsoft 365 subscription, update your applications, or resolve any compatibility or performance issues.

    To help you gauge your readiness for Copilot, we offer a Copilot Readiness Assessment, that provides a comprehensive review of your IT environment, security posture, and Copilot requirements. This yields a detailed report with recommendations and best practices to prepare for deployment and minimize errors during the process.

    The Catalyst Gets Clear on Copilot Adoption – Getting ready 

    Step 3: Run a pilot with select users, configure and implement

    The third stage of the flight path is to configure and deploy Copilot for Microsoft 365 according to best practices and your specific requirements. This is when you integrate your custom data sources, including enterprise data, industry-specific terminology, and so on.

    Then, you test and validate the functionality, performance, permissions, and security of Copilot within your IT environment with a focus on integration with enterprise data.

    Note that we strongly recommend deploying Copilot as a pilot project to a select group of users first. This gives you the chance to collect valuable user feedback and course correct where needed before going organization wide.

    To help you implement and pilot Copilot, we have a Copilot Implementation Service, including expert guidance and support to set up and deploy Copilot. This includes a Copilot Pilot Program with a custom plan and toolkit for deploying to an initial group of select users.  

    The Catalyst Gets Clear on Copilot Adoption – Implementation

    Step 4: Adopt Copilot and manage the people factor

    Copilot for Microsoft 365 won’t have any impact if people don’t know it’s there or why they should use it.

    This means a continuous management approach to end user adoption focused on realizing the actual benefits, whether that’s increasing employee productivity or transforming the way they work with their customers.

    The next phase is built to heighten awareness, engagement, and adoption of Copilot among your end users at every level. The importance of training, communication, and support to help people understand and use Copilot can’t be overstated.

    You‘ll also need a clear process to monitor and collect feedback from the users on their experience and satisfaction with Copilot and apply their feedback as you go.

    This is where our Copilot Adoption and Enablement Services come in. It’s meant to give you a detailed strategy and plan to drive user adoption of Copilot in your organization.

    It includes a Copilot Adoption Toolkit for educating, training and supporting users on integrating Copilot into daily work as well as in cultivating an “AI-first mentality.”

    Step 5: Sustain the momentum over the long term

    No genuine transformation is going to be a one-and-done effort.

    The final stage of the flight path involves proactive steps to keep the early momentum going. The aim is to avoid a drop-off in usage and ensure people truly integrate the tool into their work. This is more an ongoing journey than a destination.

    It involves reviewing and updating the vision, goals, and success criteria as your needs and priorities evolve and as Microsoft adds new features and capabilities. You’ll want to monitor and analyze the metrics against outcomes. It may be necessary to throw in additional training, guidance, and support to the users. Remember that new hires will also need to learn the specific ways your organization uses the technology.

    To help you sustain and optimize Copilot, Softchoice offers a Copilot Sustainment Service, where you can get ongoing support and guidance to maintain and enhance the performance and value of Copilot in your organization. This comes with a Copilot Sustainment Toolkit, where you’ll find the latest resources and tools to keep your users informed, engaged, and satisfied with Copilot for Microsoft 365.

    The Catalyst Gets Clear on Copilot Adoption – Sustain 

    Ready to take off with Copilot?

    You plan to adopt Copilot for Microsoft 365. Why should you trust us to help?

    We know people and technology. To succeed with Copilot deployment, you’ll need to account for both and have them work in harmony.

    We bring over 30 years’ experience as a Microsoft partner.This comes with a deep bench of Microsoft certified specialists who deliver thousands of Microsoft assessments and implementation projects every year.

    We were our own first Copilot customer. As a member of Microsoft’s Early Access Program, we were among the first companies to use Copilot in a real-world environment.

    Every Copilot needs a navigator

    Explore Copilot for Microsoft 365 services

  2. The EU has done it, the UK will probably do it, the US is considering it, and now India plans to follow suit with competition laws to regulate big technology firms, including Apple. Cupertino isn’t happy.

    India’s Digital Competition Bill is a similar piece of legislation to the EU’s Digital Markets Act (DMA) that is forcing Apple to open up its ecosystem, most visibly through support for third-party app stores. India’s bill will prevent companies from promoting their own services above those of rivals, stop them from exploiting non-public user data, and also require support for third-party app purchases.

    Free trade where we want it

    Apple isn’t the only technology firm that’s unhappy about India’s proposals. Google and Amazon are also full of rue. 

    That is why a US lobby group that represents all three big firms is pushing for India’s government to rethink its proposals, warning that the draft law goes further than the DMA. “Targeted companies are likely to reduce investment in India, pass on increased prices for digital services, and reduce the range of services,” the US-India Business Council reportedly said.  

    (The irony that the US Chamber of Commerce should make that argument, even while the US Department of Justice struggles to bring in similar constraints on Apple and other big companies, is hard to ignore.)

    A threat to Apple’s India plan?

    Threat of this new law may also displease Apple’s latest manufacturing partner, Tata, which is making big investments to stake space in Apple’s India-based iPhone supply chain. The top tech company in India by market capitalization, Tata holds a senior seat on the US-India Business Council board. Most of the country’s big names have some representation on the group. 

    In truth, Apple’s major investments in India may spell “iPhone” to the rest of us, but to those involved in its manufacturing supply chain there, the same word spells “profit” — and they are unlikely to want that nascent business beaten quite yet. 

    We shall see what happens ahead, but the stage does seem set for some wrangling over the content of the new legislation. The proposals specifically target entities with a turnover in excess of $30 billion and at least 10 million local users of digital services — which basically means the big tech firms, whose market power the bill aims to constrain.

    Apple wants to build business across the nation of 1.4 billion people and is well on the way to achieving that. As it seeks to reduce its reliance on China, the company is making huge efforts to build manufacturing centers and attract new users in India, so anything likely to make that work more challenging won’t be seen as ideal. 

    Apple CEO Tim Cook recently said the company generated record revenues in India during the March quarter, though critics may claim part of this success reflects company control of the apps market on its platforms. 

    Control of the means of production

    Wrong or right, the extent to which big firms control the digital economy is what India’s regulations, just like those elsewhere, seek to constrain. Attempts to dent such market power is very much reflected in the work of India’s Competition Commission, which has already fined Google more than $160 million over app purchases and pre-installed apps. Apple is also undergoing investigation at this time. 

    The act won’t become law immediately. The government is gathering feedback before submitting the regulations for approval by parliament, and there is no set timeline for that process to take place, according to Reuters.

    But for Apple this new attempt to regulate its business surely makes it far more likely that it will eventually be forced to open up its platforms to third-party apps on a global basis, rather than just in the EU. I don’t see that happening swiftly, however. The cautious approach would be for consumers, competitors, the company, and any sensible regulators to review the potential failures of such openings-up in Europe, where third-party stores are now opening at a trickle, rather than a flood.

    Pending further evidence, the jury remains out on the extent to which sideloading in Europe will undermine user security and privacy, or dilute the value of the user experience.

    Please follow me on Mastodon, or join me in the AppleHolic’s bar & grill and Apple Discussions groups on MeWe.

  3. China has established a massive new state-backed semiconductor fund worth 344 billion yuan or $47 billion aiming to ramp up its chip industry, according to the National Enterprise Credit Information Publicity System, a government-run credit information agency.

    This aggressive move is seen as a countermeasure against US efforts to limit China’s access to advanced chip technology.

    Christened the China Integrated Circuit Investment Fund Phase III, the investment in this phase is the largest yet and was registered on May 24. This phase dwarfed its previous two phases registered in 2014 and 2019 with investments of 138.7 billion yuan and 204 billion yuan respectively.

    The Ministry of Finance holds a 17% stake in the fund followed by a subsidiary of the state-owned National Development Bank at 10.5% and a Shanghai municipal government investment company at 9%.

    The fund also lists seventeen other entities as investors including five of China’s largest banks, including Bank of China, Industrial and Commercial Bank of China, China Construction Bank, Agricultural Bank of China, and Bank of Communications — each holding a six percent stake.

    The China Integrated Circuit Investment Fund, also known as “Big Fund,” was launched under the “Made in China 2025” initiative in 2015 as a financing vehicle to promote high-tech industrial development.

    The “Big Fund” has already provided financial support to two of China’s major chip manufacturers — Semiconductor Manufacturing International Corporation and Hua Hong Semiconductor, according to a Reuters report.

    The investment fund is also expected to finance the High Bandwidth Memory (HBM) industry and other key AI semiconductor fields, as per Chinese corporate information service, Qichacha.

    While specific targets remain undisclosed, the fund in the third phase is expected to focus on AI-related semiconductors and manufacturing equipment. The fund also aims to support R&D projects and assist major Chinese semiconductor companies in transitioning from international to domestic suppliers for key materials like chemicals, industrial gasses, and silicon wafers. This move will minimize China’s reliance on foreign suppliers and potentially weaken the effectiveness of future US restrictions.

    This move comes as the US tightens export controls on advanced chips and fabrication tools to hinder China’s tech advancements.

    In October 2022, the US implemented comprehensive export controls to curb China’s military modernization by restricting access to advanced AI chips that use US technology. Again in 2023, the Bureau of Industry and Security updated these rules to address loopholes that compromised their effectiveness.

    “Today’s updated rules will increase the effectiveness of our controls and further shut off pathways to evade our restrictions. These controls maintain our clear focus on military applications and confront the threats to our national security posed by the PRC Government’s military-civil fusion strategy,” Secretary of Commerce Gina M. Raimondo said in a statement in 2023. “As we implement these restrictions, we will keep working to protect our national security by restricting access to critical technologies, vigilantly enforcing our rules, while minimizing any unintended impact on trade flows.”

  4. The tech world lost a legend earlier this month — and it happened the same week that his life-long vision was finally realized. 

    I’m talking about C. Gordon Bell, the computer scientist who helped usher in the age of the personal computer. He designed the first microcomputer in 1965 — the DEC PDP-8 — among countless other achievements in the field of computing. Bell died May 17 of pneumonia at his home in Coronado, CA. He was 89. 

    Bell’s lifelogging vision

    Late in his career, Bell was inspired by Vannevar Bush’s hypothetical “Memex” system, which Bush described in a 1945 Atlantic Monthly articled, “As We May Think.” From that inspiration, Bell became the world’s biggest advocate and practitioner of a concept called lifelogging.

    Bell launched his lifelogging MyLifeBits project in 1998. The idea was to enter all digital content from one’s life and work. From the project page: He aimed to capture digital versions of “a lifetime’s worth of articles, books, cards, CDs, letters, memos, papers, photos, pictures, presentations, home movies, videotaped lectures, voice recordings, phone calls, IM transcripts, television, and radio.” (Bell famously wore two cameras around his neck, which snapped photographs at regular intervals.) Then, he would use custom-built software to retrieve any fact, any captured idea, any name, any event on demand. 

    MyLifeBits was part of Bell’s research at Microsoft. He joined Microsoft Research in 1995 and worked there until 2015 when he was named a researcher emeritus.

    The death of lifelogging

    Eight years ago, I interviewed Bell for Computerworld and, based on what he told me, I proclaimed in the headline: “Lifelogging is dead (for now).” What killed lifelogging, according to Bell, was the smartphone. He stopped his lifelogging experiment when the iPhone shipped in 2007.

    Smartphones, he correctly predicted, would gather vastly more data than any previous device could, given their universality and ability to capture not only pictures and user data, but also sensor data. Suddenly, we had access to vastly more data, but no software capable of processing it into a cohesive and usable lifelogging system. 

    He also correctly predicted that, in the future, lifelogging could return when we had better batteries, cheaper storage and — the pièce de résistance — artificial intelligence (AI) to help capture, organize and present the massive amounts of data. With AI, data doesn’t have to be tagged, filed specifically, or categorized. And it can respond meaningfully with natural language interaction. 

    At the time, I wrote something I still believe: “I think we’ll find that everybody really does want to do lifelogging. They just don’t want more work, information overload or new data management problems. Once those problems are solved by better hardware and advanced AI, lifelogging and the photographic memory it promises will be just another background feature of every mobile device we use.” 

    Don’t look now, but we’ve arrived at that moment. 

    Suddenly: A new wave of lifelogging AI

    Bell did his lifelogging research at Microsoft, so it’s especially poignant that within a few days of Bell’s death, Microsoft announced incredible lifelogging tools. (Company execs didn’t use the “L” word, but that’s exactly what they announced.)

    During a special May 20 event preceding the Microsoft Build 2024 conference, the company introduced its Recall feature for Copilot+ PCs, which will run Windows 11 and sport Qualcomm’s new Snapdragon X Elite chips. (They have a neural processing unit (NPU) that makes Recall possible, according to Microsoft.)

    Here’s how it works: Recall takes a screenshot of the user’s screen every few seconds. (Users can exempt chosen applications from being captured. Private browsing sessions aren’t captured, either. And specific screenshots, or all captures within a user-designated time frame, can be deleted.)

    The screen-grabs are encrypted and stored locally, and the content can then be searched — or the user can scroll through it all chronologically. The secret sauce here, obviously, is that AI is processing all the data, identifying text, context, images and other information from the captures; it can later summarize, recall and generally use your screenshots to answer questions about what you’ve been doing, and with whom. The goal is to provide you with a digital photographic memory of everything that happens on your device.

    Microsoft’s Recall feature is lifelogging, pure and simple. AI makes this lifelogging tool feasible at scale for the first time ever.

    (Copilot+ PCs start shipping on June 18, 2024, according to Microsoft.) 

    One week before Microsoft’s announcement, and mere days before Bell’s passing, Google announced lifelogging tools of its own. During a video demonstration of Project Astra, where visual AI identifies and remembers objects in the room and performs other neat tricks via a Pixel phone, the woman showing off the technology picked up AI glasses and continued with her Astra session through the glasses. 

    Astra is capturing video, which AI can process in real time or refer back to later. It feels like the AI tool is watching, thinking and remembering — which, of course, it isn’t. And it’s trivial for AI to spin out a text log of every single thing it sees, identifying objects and people along the way. AI could then retrieve, summarize, process and help you make instant sense of everything you saw. 

    Bell wore cameras around his neck to capture snapshots. It couldn’t be more obvious that glasses capturing video to be processed by generative AI is vastly superior for lifelogging. 

    Google this month also announced another powerful lifelogging tool, which I first told you about in September. It’s called NotebookLM. The AI-enhanced note-taking application beta is free to try if you’re in the United States. The idea is that you take all your notes in the application, and upload all content that comes your way, including text, pictures, audio files, Google Docs and PDFs. 

    At any point, you can interrogate your own notebook with natural language queries, and the results will come back in a way that will be familiar if you’re a user of the major genAI chatbots. In fact, NotebookLM is built on top of Google’s PaLM 2 and Gemini Pro models. 

    Like the better chatbots, NotebookLM will follow its display of results with suggested actions and follow-up questions. It will also organize your information for you. You can invite others into specific notes, and collaborate.

    NotebookLM is the lifelogging system Gordon Bell spent nine years trying to build. But his ideas were too far ahead of the technology.

    The previous two weeks will go down in history as the most momentous thus far in the life of the lifelogging ideas since Vannevar Bush described his Memex concept in 1945. Of course, in the AI era, lifelogging won’t be called lifelogging, and the ability to lifelog effectively will be seen as something of a banality — you know, like the PC and the many other digital gifts midwifed into existence by Gordon Bell. 

    I told you lifelogging was dead, until we got the AI tools. And now we have them.

  5. Americans, it seems, are of several minds about the hottest of hot topics this year: artificial intelligence. They’re torn between curiosity about the benefits to society and concern about its effects on their lives.

    A new study from global consultancy Public First found that, while the most common emotion cited was curiosity (39%), an almost equal number (37%) said they were worried about AI. Last year, 42% cited curiosity and 32% were worried, according to the study, which was based on four nationally representative polls of adults across the US and the UK, and conducted in partnership with the Information Technology & Innovation Foundation’s Center for Data Innovation.

    While awareness of AI is growing quickly, day-to-day usage is still quite low, said Jonathan Dupont, partner at Public First, in a webinar about the research. In fact, 51% of Americans said that AI is growing faster than expected, up from 42% in 2023.

    ChatGPT, he said, “is now definitely a consumer brand.”

    However, people’s emotions are mixed when it comes to concrete benefits for themselves and society, Dupont said: “The lowest thing they rated was actually increasing wages for workers, which suggests they think it might benefit society as a whole, but possibly cause unemployment concerns. They’re less convinced about it translating into actual day to day benefits for ordinary people.”

    AI at work

    Although only 28% or American workers said they have used an LLM (large language model) chatbot at work, 68% of those who had done so found them helpful or very helpful, and 38% said they have become an essential tool. Overall, this group accounted for 19% of workers.

    Age and gender made a big difference: Males aged 18-34 were by far the biggest users at 33%, while only 16% of females in that age group regularly use LLM chatbots at work. Almost half (48%) of workers using LLMs said they had figured out how to use the tools on their own, although this, too, varied by age. Workers under 55 preferred to explore the technology on their own, while those aged 55 or over expressed a desire for formal AI training.

    Respondents expected that required job skills will change, according to the study. They saw an increased need for the ability to persuade and inspire people, for critical thinking and problem solving, and for creativity. However, they felt that research, writing well, coding or programming, graphic design, and data analysis will decline in importance with the rise of AI.

    Critically, 59% believed it likely that AI will increase unemployment.

    But, said Alec Tyson, associate director of research at Pew Research Center, in the workplace, how and where AI is used will affect its acceptance.

    “Large majorities would oppose using AI to make a final hiring decision,” he said, an illustration of a broader concern about what’s essentially human. What are humans good for in the areas, whether it’s work or medicine? Your relationship with the primary care doctor that has traditionally been high contact is something close to essentially human; there’s a lot of resistance to using AI to fill those roles. There’s more openness, maybe not outright enthusiasm, but more openness to use AI to help.”

    Lee Rainie, director, Imagining the Digital Future Center at Elon University, pointed to two categories of people at the extremes of concerns about AI adoption. “One is creative people themselves,” he said. “I think by instinct they’re innovators in many cases and they’re trying to cut at the edge but I think they see an existential threat more acutely than a lot of other groups here, and watching the legal situation play out, their reactions to AI are going to be very much determined by whether they have autonomy, whether they get paid, what’s disclosed about how the language models are used.”

    The second group is people who are suffering in some way. If AI is going to help somebody, he said, there’s not a lot of hesitation about its use.

    What jobs can AI automate?

    Job loss caused by AI is also a concern. When asked to assign a score from 0 to 10 on how likely respondents felt it was that an AI could do their job as well as they could in the next 20 years, predictions were all over the map. Fully 22% said that robots or AI could not do their job, scoring the prospect at 0. At the other end of the scale, 14% said AI or robots could definitely do their job. In the middle, 14% rated the notion a 5. The average score was 4.7.

    The top four occupations at risk, according to respondents, were machine operators (46%), customer service agents (42%), warehouse workers who pick and pack goods (41%), and graphic designers (40%). At the bottom of the list were nurses and care workers, each at 10%.

    Overall, however, only 28% thought their jobs would disappear entirely. Others expected they would have other responsibilities (30%), oversee the AI (25%), or spend fewer hours on the job (27%).

    Vinous Ali, managing director at Public First, also noted that fears about unemployment vary. “I think the most interesting thing is it’s actually those with degrees, those who are higher and more educated, who feel that their jobs could be at risk, rather than those who have a high school diploma,” she said. “And I think that’s a really interesting difference to previous changes in the workplace.

    “I think the top-ranking job that seemed to be highly automated was computer programmer, so this is a real difference, and it’s a real break with the past. And so it’ll be interesting to see how that develops.”

    Bottom line

    Because AI is so new, there are limitations to the conclusions that can be drawn from the study, Dupont said.

    “This is still very much in the abstract for a lot of people, and this is still the future. Polls are always more accurate when you’re asking people about everyday concrete experiences and things they actually are using on a day-to-day basis.

    “It’s very easy to push a polling question or make people say, ‘AI is going to be the most amazing thing in the world or AI is going to be terrifying.’ And I think the general picture is, most people have very mixed views, and they don’t know. And it depends how it’s implemented.”

    “A poll is a great snapshot in time,” added Ali. “And we’ve worked really hard to make the findings as robust as possible, but clearly, there are limitations when adoption rates are so low, and there are ways that you can work around that. But this is why it’s a tracker poll. … Who knows where we’ll be in a year’s time.”

    The complete study is available on the Public First website.