Computerworld.com [Hacking News]

Toxic work environments and a lack of internal upward mobility are adding to employee dissatisfaction, and many workers believe a primary cause of the problem stems from the behavior of their managers, according to a new study by career development and outplacement firm Intoo.

The survey, conducted in partnership with research firm Workplace Intelligence, also found Gen Z employees are engaging more in “AI Career Coaching” and claim to get their best career advice from ChatGPT. Around 47% of Gen Zers say they get better advice from a chatbot than from their manager. More broadly, 77% of employees and 79% of human resource leaders said they’d experienced at least one characteristic of a toxic workplace in their jobs.

Lydia Frank, vice president of marketing at Chronus, a career development platform, said because Gen Zers were the first generation to grow up with the internet as a part of daily life, they’are accustomed to everything being a click away. “Which is why we’ve seen them heavily adopt and make use of generative AI for everything and anything. Career advice is no exception,” she said.

“Often, Gen Zers are turning to ChatGPT for career advice because they are not satisfied with their current company’s learning and development programs or lack the professional networks earlier generations were able to build when hybrid workplaces were the exception, not the rule,” she said. “We’re seeing a lot of Gen Zers that lack mentorship — especially when working remotely — which is why they’re either trying to learn a new skill or navigate a workplace situation through consulting ChatGPT,” Frank said.

Poor treatment at work and a lack of career advancement have also led to a growing number of workers to actively seeking employment elsewhere, according to the Intoo survey of 800 employees and 800 human resource leaders. The survey data, collected between Nov. 19 and Dec. 2, 2023, was originally published in February, then updated and re-released Tuesday. 

The survey focused on what makes a workplace toxic and what would create a positive work environment that leads to greater job satisfaction, better performance, and higher retention.

The top factor contributing to toxic workplaces is managers showing favoritism towards certain employees, according to 46% of employees surveyed by Intoo and Workplace Intelligence. And 42% cited managers or leaders who ignore employee feedback as contributing to poor work environments.

Adding to the problem: bad advice from managers, according to the survey data. More than a third (39%) of workers said they’d received bad career advice from managers. In fact, employees said they get better career advice from their friends and family (62%), Google (44%), social media (36%), and genAI (34% overall) than they get from their boss.

According to Intoo’s survey, 63% of respondents felt their employer cares more about productivity than career development, and 54% said they feel completely on their own at their organization when it comes to career development. Forty-four percent said their employer does not value their career development.

In tandem with those sentiments, HR leaders in the survey predict that 25% of employees (and 44% of Gen Z employees) are likely to quit their jobs within the next six months due to a lack of support for career development.

Career path confusion

A separate workplace study done by recruitment and outplacement firm LHH found that nearly half of 30,000 full-time employees in 27 countries (46%) want to change careers — but don’t know which path to take. And 72% of workers contemplate future plans — such as their next job, reskilling, and upskilling — at least once a quarter.

A majority of workers (86%) are confident that they could find a new job within six months up, from 61% in 2022, whether it’s through their own networks (74%), independent job search (71%), or a staffing agency (68%), according to the LHH survey. But nearly half (46%) don’t feel their managers would support them in moving to another role within the organization.

Additionally, 47% are keeping up to date with open job opportunities, yet not applying for them, according to LHH data. However, another 18% are actively applying for jobs and 19% indicated they’re interviewing with prospective employers. Only 8% are looking for new opportunities internal to their company.

Among other big takeaway from LHH’s report? Organizations need to invest in their employees in order to attract skilled talent, especially from tech. “Workers in tech are the most confident that their skills can transfer to another industry or to another role within the tech field,” the report said.

The broader sense of unease is shared across geographies and industries, especially in Australia (65%), China (62%), Turkey (59%), and the US (57%), where workers feel strongest that external factors affect their careers more than they do themselves. In these countries, employees are less likely to quit for salary reasons than because they want to start their own businesses, showing they want to feel empowered.

Many younger employees make career decisions based on their values and want to be able to drive change within their organizations, but feel powerless to do that, according to a recent survey by Deloitte. Over half of respondents (58% of Gen Zs and 55% of millennials) say their organization currently seeks input from employees and incorporates their feedback, but roughly a third (32% of Gen Zs and 35% of millennials) say decisions are still made from the top and employee feedback is not often acted upon.

Careers, IT Leadership, Technology Industry

At its Adobe Max event in London, Adobe on Tuesday unveiled its latest Firefly Image generative AI (genAI) model, promising greater realism and improved controls over generated outputs. The next-generation Firefly model will also be integrated into Photoshop, with several new features coming to the image editor later this year. 

Adobe Firefly is a set of generative AI models used to create and modify content such as photographic style images, illustrations, and fonts. (A Firefly video-generation model is coming to the Premier Pro video editing tool later this year, with a music-generation algorithm also in the works.) It’s accessible as a standalone app, as well as being integrated into Adobe’s Creative Cloud application suite. 

More than a year since launch, Firefly’s Image model is now on its third iteration. Firefly Image 3 improves on the second iteration, which launched at last October, in several ways, said Adobe. 

The company highlighted improvements to image quality, particularly for images that feature people. That means more photo-realistic outputs, better lighting and subject positioning, and a wider variety of expressions. Another quality improvement is involves rendering straight lines and structures that help with image coherence.

Adobe Firefly generated image of an artist in studio.

Adobe

The latest model includes the Structure Reference feature that Adobe announced last month; it lets users apply the structure of a reference image to provide more accurate outputs. The same goes for Style Reference, which helps create a consistent image style.

Users can also expect a broader range of output styles for illustrations, photographic art, and vector art for iconography. Firefly Image 3 will have a better understanding of user prompts, too, Adobe said, more accurately reflecting longer and more complex inputs than the previous versions.

“Firefly Image 3 is a considerable level up from the already high-performing Firefly Image 2 model,” said Matt Arcaro, IDC research director for computer vision and AI, with notable improvements to image quality and coherence with user prompts. 

Firefly Image 3 also gives users greater control over images produce by the AI model, said Liz Miller, vice president and principal analyst at Constellation Research. “If Firefly Image 1 and 2 focused on the ability to generate, Firefly Image 3 is about focusing and controlling generative AI models to extract the idea in a creator’s mind onto the initial canvas,” she said.

Adobe is one of numerous tech firms that offer genAI image models, including  Canva, Midjourney, OpenAI, Stability AI, and others. IDC predicts that global spending on genAI tools (including software and infrastructure) will reach $143 billion in 2027, up from $16 billion in 2023. 

“Firefly Image 3 may be in beta, but feels less experimental compared to some of Adobe’s rivals,” said Miller. The latest Firefly model is more photo realistic and addresses some of the problems creators have experienced with generative AI tools around structure, she said – producing images of arms with two hands, for instance. 

Firefly Image 3 is available now in beta via the Firefly web app.  

New Firefly features in Photoshop

Another strong point for Adobe’s generative AI capabilities is integration across its products, said Arcaro. “Adobe is all-in on bringing genAI capabilities to users across its product portfolio,” he said. 

Adobe said the Firefly Image model and new genAI features will arrive for Photoshop later this year, building on Generative Fill (the mostly quickly adopted feature in ever in Photoshop, according to Adobe) and the Generative Expand tools added to Photoshop a year ago.  

The idea is to improve workflow when accessing genAI features in Photoshop. 

For example, Reference Image lets users tailor Generative Fill images to a particular style by uploading a reference document. This lets users guide the Firefly’s outputs more accurately and saves time typing out text prompts to create a desired image. 

Adobe Firefly makes it easier to manipulate and use reference images with genAI.

Adobe

Another feature, Generate Image, lets users create entire images from scratch in Photoshop documents using text prompts. The intention is to make the image editor more accessible to users of any skill level, said Adobe. The Generate Image tool provides options for content type, effects, and allows users to upload a reference image. 

Generate Background makes it easier to replace or create background visuals in an image using natural language prompts. While it’s already possible to generate background images in Photoshop, the new feature is more streamlined and requires fewer clicks, Adobe said.

Generate Background allows users to create background visuals  using natural language prompts.

Adobe

Generate Similar provides variations of objects within an image from which users can select, such as the amount or type of fruit in a fruit bowl, allowing for greater fine tuning of results. 

Generate Similar using Firefly offers variations of objects within an image.

Adobe

Finally, Enhance Detail lets users increase the sharpness and clarity of generated images.

The features are available in the beta Photoshop app — a separate application that  showcases new capabilities — before general availabilty later this year, said Adobe. It will be possible to run the AI processing either on Adobe’s servers or locally on a user’s device, with cloud computation the default. 

“These tools are all about efficiency and shifting monotonous work off a creator’s plate,” said Miller. Getting from a brief to a sketch to a draft can be a painful, time-consuming, and costly process, she said.

“The traditional pace of creation takes a toll, especially when the language of creativity can get lost in translation…,” Miller said. “With these tools native in Photoshop, creators can ideate and iterate quickly, collaborating on color tones, shape and structure in a rapid flow.”

Adobe Systems, Generative AI, Productivity Software

While the employee benefits of the AI PC are intriguing, they may not be enough to convince IT buyers to go all in just yet, according to a Forrester report.

Despite the enthusiasm generated by PC vendors and chipmakers at the 2024 Consumer Electronics Show, where advanced AI-driven functionalities were prominently featured, enterprises are expected to adopt a more measured approach over the next year, Forrester said in the report.

The Promise of AI PCs

AI PCs are designed to enhance enterprise users’ productivity, cost efficiency, and security. By processing sophisticated AI applications locally, these PCs reduce reliance on costly and often slower cloud services. This could be especially beneficial in sectors such as finance and healthcare, where operations heavily depend on data processing and where data privacy and security are of the utmost importance.

The ability to process data locally on an AI PC minimizes the risk of breaches and helps enterprises comply with stringent regulatory requirements.

Challenges in adoption

Despite the benefits, the adoption of AI PCs among enterprises is fraught with challenges. “CIOs face several barriers when considering AI-powered PCs, including the high costs, difficulty in demonstrating how user benefits translate into business outcomes, and the availability of AI chips and device compatibility issues,” said Andrew Hewitt, Principal Analyst at Forrester Research.

CIOs feel they are struggling to show a return on investment in AI PCs. Limited business use cases for enterprises make it challenging to justify the use of these powerful machines, which are mostly restricted to niches like “gaming or content creation,” said Abhishek Gupta, Dish TV’s CIO.

“AI PCs are still very new with only a handful of options available across brands and at a premium price. The higher prices of AI PCs along with lack of enough use cases, is stopping CIOs from the adoption of AI PCs,” Gupta said.

“Businesses should look beyond impressive hardware specifications—they need genuine, measurable returns on investment,” said Ankush Sabharwal, CEO of CoRover.ai, a human-centric conversational and generative AI platform. “There is no denying that AI platforms are advancing rapidly, and this progress is paving the way for practical, problem-solving AI applications that go beyond mere gimmicks. We already have the necessary technology; the focus now should be on developing AI applications that are tailored for specific devices and industries rather than adopting generic, one-size-fits-all solutions.”

Future projections and enterprise readiness

Enterprise readiness to adopt AI PCs often coincides with major OS updates to avoid compatibility issues. Forrester’s 2023 data shows that over half of infrastructure hardware technology decision-makers report that 50% or fewer of the company-issued PCs run on Windows 11. This suggests a broader hesitation towards rapid technological upgrades.

Windows 10’s anticipated end-of-life in October 2025 is expected to coincide with the increased adoption of AI PCs. “Enterprises will likely align their hardware upgrades with the new capabilities offered by the latest operating systems, which will be optimized for NPU technology,” Hewitt said.

Hewitt has predicted a tripling of AI platform budgets in 2024 to accommodate the burgeoning demand for AI applications. This budget expansion is anticipated to catalyze the adoption of AI PCs, especially as enterprise workloads continue to depend on cloud services, which are expected to become more costly. This presents a compelling case for the increased use of AI PCs in digital workplaces.

The next 18 months are crucial for AI PCs, according to CoRover.ai’s Sabharwal. “Instead of just purchasing hardware, shifting the focus towards utilizing AI to address industry-specific challenges is essential. For instance, Small LLMs can be trained to operate efficiently on AI PCs. Startups, particularly cloud-native ones, are the pioneers in adopting this technology. “As chip technology progresses and costs decrease, we anticipate a tipping point where investing in AI-based PCs will become justified.”

Upcoming chipsets with higher processing capabilities will drive further interest in AI PCs across data-intensive sectors such as manufacturing and high-tech, Hewitt said. “Industries that blend creative work with data science are prime candidates for early adoption,” he noted.

Impact on cloud services

As AI PC adoption potentially reduces reliance on cloud computing, cloud providers may have to adjust their pricing models. Hewitt suggests a likely shift towards a hybrid model where some processing will continue in the cloud while other tasks move to local AI PCs. This adjustment would balance cost concerns with enhanced security and privacy benefits.

Despite the potential and capabilities demonstrated by AI PCs, 2024 is shaping up to be a year of gradual exploration and tentative adoption by enterprises. As AI technology continues to evolve and more tailored applications become available, the pace of adoption is expected to accelerate, making AI PCs an integral part of enterprise technology ecosystems in the near future. This cautious but steady approach reflects the enterprise’s strategic planning in integrating cutting-edge technologies into its operations.

Windows PCs

The four-day work week was unthinkable, except in science fiction, as recently as five years ago. But one of the many things the COVID-19 pandemic taught us is that the structure of the workplace can change significantly and still be viable. That realization has opened the door to considering a work week of four 10-hour days or even 32 hours as a real possibility. 

The idea has been around since at least the 1950s; but until recently, it hasn’t been taken seriously.

A 2024 KPMG poll of 100 US CEOs found that nearly one-third of US companies are exploring the idea of dropping one day a week. That may sound unimpressive at first, but think about it for a moment. Let it sink in. 

This is only the vanguard.

Four-day week trials and studies have been surprisingly positive for both employees and employers. The large UK four-day work week pilot program was so successful that, of the 61 firms that participated, 92% said they would continue their four-day work week beyond the trial, including 29% that had already decided to make the change permanent. Earlier studies were also successful. And several companies have reported success in many facets of their business with their own trials, such as US-based Exos.

Employees are receptive to the idea. A Washington Post-Ipsos conducted a year ago showed that 75% of US workers would rather work four 10-hour days than five eight-hour days for the same pay. Meanwhile, according to a survey by cloud-software vendor Qualtrics, 92% of US workers are in favor of a shortened work week, even if it means working longer hours each day.

European countries may be ahead of the curve on shorter work weeks, with the UK and Germany undertaking large-scale trials; Iceland, Portugal, and Spain are also running pilot programs; and Belgium is the first country to pass a law that gives workers the option to work a four-day 40-hour week.

Analyzing the benefits

A shortened work week can help companies attract top talent, boost employee retention, reduce employee stress, lower the carbon footprint of employees (and potentially that of the company), and save employees money on commuting and childcare. The largest benefit, however, is a major boost to work-life balance, which appears to foster an increase in work productivity. (Check out this list of pros and cons of the 4-day work week.) 

The concurrent arrival of a host of generative AI tools should also bolster productivity, mitigating any risks when switching to a four-day work week. 

Those who oppose the notion might see productivity as chiefly measured by time — so many minutes equals so much productivity. And that might be true for assembly-line manufacturing, for example; the four-day work week isn’t for every company.

For many other jobs where what’s being created is intellectual property, ideas, strategic plans, sales, marketing, and software, for instance, intellectual acuity is the essential ingredient — and burn-out is a very real challenge in such roles. To be sharp, you need to be well-rested in mind and body. A four-day work week could well boost productivity in that kind of environment. 

Even before the pandemic, some companies had begun to loosen up. Casual Fridays became work-at-home Fridays, for instance. Switching to working four days a week seems like a natural progression in that scenario.

So, it’s not surprising that a common finding of many four-day-work-week trials is that employee productivity grows, even in 32-hour weeks. More days in a week allows for more meetings, more distractions, more long lunches, and more employee procrastination. Fewer days in a week forces employees to sharpen their time-management skills and focus on completing tasks. Getting your mind out of the job for three days recharges your batteries and brings new perspective to your work, which in turn can elevate productivity.

Implementing a four-day work week

To ensure this change is successful, companies can’t just flip a switch and suddenly tell everyone that they work four days a week. According to the Harvard Business Review, four-day work week initiatives “only work if companies undertake substantial work redesign to reduce hours while maintaining business outcomes. This means streamlining operations, removing administrative burdens, and prioritizing high-impact work.” 

For more information about successfully planning a four-day work week trial or roll-out, here are useful resources:

• How to implement a 4-day work week, according to a CEO —  Fast Company

• A guide to implementing the 4-day work week –— Harvard Business Review

• How to implement a 4-day work week for the whole organization –— MIT Sloan

• Four-day week: how workplaces can successfully establish it — The Conversation

• The 4-day work week schedule – An Implementation  Guide — Shiftbase

The future of work is a complex vista of remote work, hybrid work, return to office mandates, and flexible working arrangements affected by trends like genAI and the pursuit of work-life balance. A shorter work week is a significant alternative in the mix that could reshape work as we know it. What exactly that will look like is hard to predict, but it’s likely the four-day work week will play a leading role.

IT Strategy, Productivity Software, Technology Industry