Information Week

AI development, like the technology itself, is still in its early stages. This means that many development tools are also emerging and advancing.  Over the past several months, we’ve seen the rise of a new technology stack when it comes to AI application development, as the focus shifts from building machine learning models to building AI solutions, says Maryam Ashoori, director of product management for watsonx.ai at IBM, in an email interview. “To navigate exponential leaps in AI, developers must translate groundbreaking AI research into real-world applications that benefit everyone.”  Essential Tools  Current AI tools provide a comprehensive ecosystem supporting every stage of the AI development process, says Savinay Berry, CTO and head of strategy and technology at cloud communications services provider Vonage, in an online discussion. A wide array of tools helps developers create and test code, manage large datasets, and build, train and deploy models, allowing users to work efficiently and effectively, he notes. “They also facilitate the interpretation of complex data, ensure scalability through cloud platforms, and offer robust management of data pipelines and experiments, which are crucial for the continuous improvement and success of AI projects.”  Related:IT Pros Love, Fear, and Revere AI: The 2024 State of AI Report Within the current AI landscape, there are a variety of essential development tools, Ashoori states, including integrated development environments (IDEs) for efficient coding, version control tools for collaboration, data management offerings for quality input, cloud platforms for scalability and access to GPUs, and collaboration tools for team synergy. “Each is critical for streamlined, scalable AI development,” she says.  Every AI developer should have a minimum set of tools that cover various aspects of development, advises Utkarsh Contractor, vice president of AI at generative AI solutions firm Aisera and a generative AI senior research fellow at Stanford University. “These include an IDE such as VS Code or Jupyter Notebook, a version control system like GitHub, and open-source frameworks like PyTorch and TensorFlow for building models.” He believes that data manipulation and visualization tools, like Pandas, Matplotlib, and Apache Spark, are essential, along with monitoring tools, such as Grafana. Contractor adds that access to compute resources and GPUs, either locally or in the cloud, are also critical for quality AI development.  GitHub Copilot, an AI-assisted programming tool, isn’t essential but can enhance productivity, Contractor says. “Similarly, MLflow excels in tracking experiments and sharing models, while tools like Labelbox simplify dataset labeling.” Both are valuable additions, but not required, he observes.  Related:Keynote Sneak Peek: Forrester Analyst Details Align by Design and AI Explainability When it comes to cloud services, Berry notes that tools such as AWS SageMaker, Google Cloud AI Platform, Google Colab, Google Playground, and Azure Machine Learning offer fully managed environments for building, training, and deploying machine learning models. “These platforms provide a range of automated tools like AutoML, which can help developers quickly create and tune models without deep expertise in every aspect of machine learning,” he says. “They are particularly valuable for developers who want to focus more on model development and less on infrastructure management.” Berry adds that these tools add value by streamlining processes, enhancing collaboration, and improving the overall user experience, even if they aren’t strictly required for all AI projects.  When it comes to scaling AI development at the enterprise level, organizations should look beyond disparate development tools to broader platforms that support the rapid adoption of specific AI use-cases from data through deployment, Ashoori advises. “These platforms can provide an intuitive and collaborative development experience, automation capabilities, and pre-built patterns that support developer frameworks and integrations with the broader IT stack.”  Related:Sidney Madison Prescott Discusses GenAI’s Potential to Transform Enterprise Operations Fading Away  As AI evolves and new tools arrive, several older offerings are falling out of favor. “Some libraries, such as NLTK and CoreNLP for natural language processing, are losing relevance and becoming obsolete due to innovations like generative AI and transformer models,” Contractor says.  “Once the go-to for data analysis, Pandas and NumPy, two popular Python libraries for data analysis and scientific computing, are losing adherents,” observes Yaroslav Kologryvov, co-founder of AI-powered business automation platform PLATMA via email. “Theano, replaced by TensorFlow and PyTorch, has suffered a similar fate.”  As AI development continues to advance rapidly, staying updated with the latest tools and frameworks is crucial for maintaining a competitive edge, Berry says. “While some older tools may still serve specific purposes, the shift toward more powerful, efficient solutions is clear,” he states. “Embracing innovations ensures that AI developers can tackle increasingly complex challenges with agility and precision.”  Adaptability and Streamlining  In the rapidly evolving AI universe, developers must maintain a high degree of adaptability, continuously reassessing and optimizing their toolsets, Contractor says. “As innovation accelerates, tools that are essential today may quickly become outdated, necessitating the adoption of new cutting-edge technologies and methodologies to enhance workflows and maximize project efficiency and effectiveness.”  To simplify and streamline the AI development experience, organizations should seek platforms that provide developers with optionality, customization and configurability at every layer of the AI stack, Ashoori concludes.  source

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The outcome of the US presidential election will not be the end of cyberthreats from bad actors who might be backed by aggressor nation states. Geopolitical tensions will persist on the domestic and international stages with the potential for enterprises to be targets. Denial of service attacks, ransomware, and other forms of digital malice stand to be in play for the sake of political agendas, though money can play as much a role in hackers’ motivations as ideology.     Hacktavists and other bad actors backed by aggressor states will continue to be in play well after the election as geopolitical tensions continue. What types of organizations might find themselves to be targets (perhaps again) after the election? This episode of DOS Won’t Hunt brings together Carl Wearn, (upper left in video) head of threat intelligence analysis and future ops at Mimecast; Robert Johnston, (lower right) co-founder and CEO of Adlumin; Mike Wiacek, (lower center) CEO of Stairwell; Armaan Mahbod, (lower left) vice president of security and business Intelligence with DTEX Systems; and Adam Darrah, (upper center) vice president of Intelligence with ZeroFox. They discussed ways organizations might orient their cybersecurity and defenses for the post-election world, the prevalent types of attacks launched on behalf of aggressor states, and how the current cybersecurity infrastructure measures up to the potential threats that are in play. Related:2024 Cyber Resilience Strategy Report: CISOs Battle Attacks, Disasters, AI … and Dust Listen to the full podcast here. source

“Harnessing Mainframe Data for AI-Driven Enterprise Analytics“ Tuesday, November 12, 2024 at 1:00pm EDT Did you know that 92% of IT leaders are actively investing in Artificial Intelligence (AI) to advance data and analytics initiatives, with an average of 5 projects either planned or ongoing? And despite the critical importance of mainframe data, only 28% of organizations report extensive use of such data for their analytical endeavors. These initiatives require data to fuel the AI and analytical models behind them, but where does mainframe data fit into the equation? Join us for a discussion on Rocket Software & Foundry’s research findings from our study, “The Role of AI and Mainframe Data in Enterprise Analytics.” This webinar is for Data & Analytics decision makers looking for knowledge of how to better integrate AI and mainframe data, overcoming prevalent challenges to unlock the full potential of enterprise analytics. Speakers: Ray SullivanVice President, Product ManagementRocket SoftwareRay Sullivan is the Vice President of Product Management for Rocket Software’s Data Modernization business. She has spent her career in Product Management, Product Marketing and Product Strategy in the enterprise software and consumer electronics industries. Ray drives Rocket’s strategy for the Structured Data portfolio, helping customers leverage and scale their data assets to deliver valuable business outcomes throughout their data modernization journeys. She also steers business and technical strategy to drive and expand technical partnerships. Lauren ZachariasDirector, Solution & Customer MarketingRocket SoftwareLauren Zacharias is the Director of Solution & Customer marketing for Rocket Software’s Data Modernization business. She has spent her career in Product Marketing, Customer Marketing, Content, and Product Development for B2B and B2C companies of different sizes in the Technology, Software, Retail, and Financial Services industries. Her specialty is creating strategic messaging for businesses that helps connect their product solutions with key buyers. Lauren has certifications and professional certificates from the Pragmatic Institute, Google, and the Product Marketing Alliance. Moderator:Peter Krass,InformationWeek  Offered Free by: Rocket Software See All Resources from: Rocket Software source

The United States experienced 28 disasters, including storms, flooding, tornadoes and a wildfire, that cost more than a billion dollars each in 2023, according to the National Oceanic and Atmospheric Administration (NOAA). And those were only the most expensive, weather-related events in one country. Around the world, natural disasters, including non-weather-related phenomena such as earthquakes and tsunamis, wreak havoc on human life and on infrastructure — including the IT that keeps life in the digital age running smoothly.   While the devastation caused by massive events understandably captures headlines, even relatively minor natural disasters such as large storms can affect IT operations. A 2024 report found that 52% of data center outages were the result of power failures. In the last decade, 83% of major power outages were weather-related. Even relatively minor storms can take out power lines.  Fourteen percent of respondents surveyed for InformationWeek’s 2024 Cyber Resilience Strategy Report said that their network accessibility had been disrupted by severe weather or a natural disaster. Sixteen percent ranked natural disasters as the single most significant event they had experienced.  Some businesses affected by natural disasters don’t survive in the first place: according to the Federal Emergency Management Agency, 43% of businesses never reopen and almost a third go out of business within two years. Loss of IT accessibility for nine days or more typically results in bankruptcy within one year.   Related:Why Businesses Need to Update Their DR Plan Now Only 23% of respondents to a survey on the effects of Hurricane Sandy in 2012 were prepared for the storm. Despite the increasing prevalence of weather-related events because of climate change, the US Chamber of Commerce Foundation found that only 26% of small businesses have a disaster plan in place as of this year, suggesting that few have planned for how their IT will be impacted.  Here, InformationWeek investigates strategies for keeping IT operational when disaster inevitably strikes, with insights from data center operator DataBank’s senior director of sustainability, Jenny Gerson, and industrial software company IFS’s chief technology officer for North America, Kevin Miller.    Preventing Damage to Infrastructure  Depending on the location of an IT facility and the natural disasters common to the region, any number of steps may need to be taken to prevent damage to essential physical IT components.   “We take into account all kinds of natural disasters when we’re looking at where to site a data center — we try to site it in the safest place we can,” Gerson says.  Related:Dust Bunnies on the Attack: Datacenter Maintenance Issues Pose Security Threats Jenny Gerson, DataBank In earthquake-prone regions, buildings need to be able to withstand temblors — additional reinforcements may be needed to prevent servers and wiring from being disrupted. Operators in areas prone to severe storms and hurricanes may need to both stormproof their buildings and ensure that essential equipment is located above ground level or in waterproof enclosures to avoid potential flood damage. Flood barriers may be advisable in some areas. Attention to potential mold damage after flooding may be necessary, as mold may create dangerous conditions for employees. And fire suppression systems may be able to mitigate damage before equipment is completely destroyed.  Using IoT sensing technology can provide early warning of disaster events and keep an eye on equipment if human access to facilities is cut off. Sensors and cameras can be helpful in determining when it may be appropriate to switch operations to other facilities or back up servers. Moisture sensors, for example, can detect whether floods may be on the verge of impacting device performance.  But, Miller notes, IoT devices can sometimes fail. “We’re seeing customers who are starting to rely more on options like Starlink,” he says. “There’s no physical infrastructure other than a mini satellite dish that’s providing that connectivity — but [it offers the] ability for them to get data, feed it back, analyze it, and then make predictive assessments on what they should be doing.”  Related:Revisiting Disaster Recovery and Business Continuity Onsite generators, including sustainable onsite power plants using solar or wind, and microgrids can keep operations running even if access to the main grid is cut off. And redundancy in cooling is crucial for data centers as well.  “Should the utility go down, we have a seamless way to get to our generator backup so there are no blips in power,” Gerson claims. “We always have backup cooling systems.”  Creating Backups  Geodiversity can make or break IT operations during a natural disaster. While steps can be taken to protect operations, they may not always be sufficient to prevent interruption. If a data center or other IT operation is taken offline, the ability to switch over to a location in an unaffected area or to more dispersed, cloud-based operations, can be relatively seamless if proper planning is in place.  This type of redundancy requires careful implementation of regular backups — cloud technology makes this relatively efficient but hard backups may be useful as well. Setting shorter recovery point objectives, while potentially more expensive in the short-term, will likely make it easier to get things back up and running if an operation is taken offline by a disaster.  IoT devices may be helpful in recovering data that is not fully backed up. Many of these devices store data on their own before transmitting portions of it to the servers to which they are connected. In the case of a disaster, that stored information may be helpful in data restoration processes.  Regulatory Compliance  In disaster-prone regions, it is advisable to proactively facilitate relationships with government authorities and emergency response agencies. This can be helpful both in ensuring continued compliance and assistance in the event of a natural disaster.   “There are certain aspects of [disaster response] that need to be captured,” Miller says. “A lot of times in crisis mode, that becomes a secondary focus. But [disaster management] systems allow the tracking and the recording of that information.”  Being aware of deadlines for compliance reporting and being in contact with

When it comes to service outages, data breaches or systems failures, there is typically only one thing IT leaders can say with total confidence: This won’t be the last time.   No matter how effective your tech and security investments are, risks cannot be entirely precluded. And if a crisis does occur, it can not only demonstrate your effective planning — but it can also be turned to your advantage.   For example, let’s turn to an area that few people would associate with an appetite for risky behavior. Economics is famous for advancing “one crisis at a time” and CIOs could benefit by taking a leaf out of its (many) books. Like firefighters battling a fire, the immediate job for CIOs is to put out the flames. Once the situation is under control, teams need to forensically identify what sparked it off in the first place, so that they can help prevent future issues.   Events such as a major outage are a signal for CIOs to consider:  Using the crisis as a catalyst to make the case for funding for cost avoidance, risk mitigation and foundation investments;  Focusing on who are your partners and who are your vendors;   Analyzing your non-financial response measures   A Crisis as Catalyst   One of the toughest things for CIOs is to get funding for issues that haven’t yet occurred. Who among us likes paying for problems that haven’t yet happened? Cost avoidance can seem hypothetical versus solving problems that are clear and present dangers.   Related:2024 InformationWeek US IT Salary Report: Profits, Layoffs, and the Continued Rise of AI The costs for those immediate challenges are usually more obvious. And mitigating the issues before they occur may be much more cost-effective and these risks may be much more than financial.   CIOs can not only learn from the experience of others, but they can use it to show how their tech investments are securing their business and saving them financial and reputational damage.  Partners or Vendors?   There is a major shift to outcome-based contracts in the tech industry, largely driven by developments such as generative AI. The latter is now realizing its potential to boost productivity, which is altering traditional value propositions. Traditionally, vendors were paid based on the volume of work or hours done. However, the new model emphasizes compensation based on the achievement of specific outcomes, such as cost reductions or revenue improvements. This approach not only aligns the vendor’s incentives with the client’s goals, but it also means that vendors take on a greater share of risk. The subtle shift here is away from the typical buyer-vendor relationship toward a technology partnership. Of course, this can be a powerful thing: Both organizations become deeply invested in the project’s success, sharing in both the risks and rewards. Related:Curtail Cloud Spend With These Strategies However, it won’t eliminate all risk. Both the client and vendor need to think clearly about how their collaboration will work beyond just the technical capabilities. Both organizations will need to consider if their corporate cultures are aligned, along with their shared vision for the project. Tech leaders need to consider if their potential partners are not only capable of driving innovation but are also culturally attuned to foster a collaborative and sustainable relationship. They may likely be sharing headlines together — in good times or bad. So how will that feel, and to what degree will it impact each company’s brand, identity and customer trust?    It is imperative for companies to establish clear risk-mitigation strategies. And they will need to have agreed, robust frameworks that ensure continuity and reliability, even when unexpected disruptions occur.  A Focus on the Non-Financials   When it comes to contracts, tech leaders focus on mitigating risk and discussions tend to revolve around “who pays if X goes wrong.” There is one aspect, though, that they need to feel total ownership over: their company’s public reputation.  Related:Forrester Speaker Sneak Peek: Analyst Jayesh Chaurasia to Talk AI Data Readiness Companies need to have thorough restorative plans for when something does go wrong — including how they mitigate customer and public impact and perception. In the wake of a crisis, CIOs need to consider how they respond immediately so that customers and clients feel supported.   To effectively prepare for inevitable incidents, companies need a rapid reaction plan. This plan should prioritize customer support, ensuring that clients feel adequately supported during disruptions.   What’s on the CIO’s Mind   There is an evolution taking place in the role of the CIO. As the role of technology has expanded in business, it has created an isomorphic effect in the IT function. The CIO’s role has also grown in importance and scope: They need to consider how to grow from being an effective cost manager to being a growth driver. Similarly, that shift toward outcomes-based contracts means that tech leaders are now being judged on costs but also on non-financial outcomes.   In my experience, ambitious tech leaders typically operate in two mindsets.   Like most C-suite leaders, to some extent they are considering their next step or role, perhaps with a bigger organization. That may be beyond the CIO function or they may be considering evolving that function to a new form altogether.   The second mindset is more concerned with legacy: As a C-suite leader, they don’t just want to keep the lights on, they want to make an impact that their name will be tied to. This will be a major move, driven by technology and perhaps requiring an acquisition, a significant investment, a people transformation program, or all of the above.   Whether you are trying to reach the next level or create a legacy, having the right risk-mitigation strategy, partners, and both financial and non-financial response is a key building block. A little trouble might just be what you need to reach your goals.  source

A hacker on Tuesday managed to briefly commandeer a National Press Club-hosted zoom broadcast featuring Ukrainian officials and others about Russian disinformation — broadcasting explicit pornographic videos. The Institute for Democracy and Development (PolitA) and the Coalition Against Disinformation organized the event, featuring Ukrainian officials, religious leaders, cybersecurity experts, and political experts discussing the ongoing and escalating Russian disinformation targeting the West and other parts of the world. An extremely graphic pornographic video with the words “CCP ON TOP” was shown on the main presentation screen for a couple of minutes before event organizers regained control. One attendee commented in the chat, “the hand of Moscow.” Live attendees at the Washington, D.C. National Press Club were also exposed to the video. Russia is pouring millions of dollars into a broad disinformation campaign meant to destabilize western governments, stoking partisan fires using fake images and stories attractive to political extremists and conspiracy theorists, the panels said. While this effort has been active for decades, it has gained significant momentum and sophistication in the past several years. Kateryna Odarchenko, president of PolitA and a political consultant, said Russia’s disinformation attempts are at an all-time high as the US elections draw near and the two-year Ukraine war rages on. “I have a background in election organizing and direct consulting, and we worked in Ukraine, we worked in Georgia, we worked in Bulgaria and with the European Parliament a lot,” she said. “From a practical point of view, we saw that Russian intervention in elections and disinformation is horrible … and it’s very effective.” Related:2024 Cyber Resilience Strategy Report: CISOs Battle Attacks, Disasters, AI … and Dust Panelists said Russia is targeting religious communities and western governments with operatives using social engineering and active cyberattack campaigns to promote chaos and is particularly active during election cycles, with the US presidential election just days away. Russia is believed to be behind the massive hack of the Democratic candidate Hillary Clinton’s 2016 campaign. ‘Zoom-Bombing’ As more and more organizations turned to video chats during the COVID-19 pandemic, the “zoom-bombing” phenomenon gained traction. The term refers to the unwanted takeover of the main presentation screen, sometimes used to display offensive or pornographic images or videos. While the culprits have ranged from internet trolls to so-called “hacktivists,” nation-state actors may be getting in on the action. Related:Juliet Okafor Highlights Ways to Maintain Cyber Resiliency In 2020, a Zoom-bombing attack targeted a US government meeting, according to a blog post by cybersecurity firm Bitdefender. “The FBI issued a stark warning … regarding the use of Zoom and dangers of Zoom-bombing, followed by advice to avoid using the platform for government affairs,” according to the blog. Zoom in 2022 agreed to a massive $85 million payout for a class-action lawsuit over Zoom-bombings. The FBI recommends the follow steps to avoid being zoom-bombed: Do not make meetings or classrooms public. In Zoom, there are two options to make a meeting private: require a meeting password, or use the waiting room feature and control the admittance of guests. Do not share a link to a teleconference or classroom on an unrestricted publicly available social media post. Provide the link directly to specific people. Manage screensharing options. In Zoom, change screensharing to “Host Only.” Ensure users are using the updated version of remote access/meeting applications. In January 2020, Zoom updated their software. In their security update, the teleconference software provider added passwords by default for meetings and disabled the ability to randomly scan for meetings to join. Lastly, ensure that your organization’s telework policy or guide addresses requirements for physical and information security. Related:Beyond the Election: The Long Cybersecurity Fight vs Bad Actors source

Developer productivity depends on more than just how quickly code is written. Communication, collaboration, and achieving the “flow state” — where developers feel fully focused and energized — are equally important to maximizing efficiency.  Technologies such as AI-augmented software, cloud-native platforms, and GitOps streamline development, automating workflows, and boosting collaboration for higher productivity.  Esteban Garcia, managing director, Microsoft Services Americas at Xebia, explains via email that it’s easy to assume developer productivity tools exist simply to help developers write more code, but he considers that a narrow view. “True productivity isn’t about producing more lines of code but about creating value efficiently, with a focus on quality and innovation,” he says.  He adds that productivity tools should simplify workflows, reduce friction and enhance collaboration — not just push developers to output more. “These tools can help improve focus, automate repetitive tasks, and facilitate smoother communication, all of which reduce stress and prevent burnout.”  Boosting (and Measuring) Productivity   Stephen Franchetti, CIO of Samsara, explains via email that GenAI is already paying dividends in the productivity space — with copiloting, code generation, quality assurance (QA) and documentation — easing the burden of the repeatable aspects of these tasks.  Related:2024 InformationWeek US IT Salary Report: Profits, Layoffs, and the Continued Rise of AI “It’s also a leadership challenge,” he says. “How do you ensure that developers not only have the right tools, but also the space to work on the most important priorities?”  He adds that developer productivity can be hard to measure as no single metric provides a complete view of performance. “Instead, tracking various indicators can reveal trends over time, whether improving or declining, but these should be viewed as individual data points rather than a holistic measure of team performance.”   When used alongside metrics that assess business impact — such as whether the projects are driving the intended outcomes — IT leaders can gain a better understanding of developer contributions.   Metrics like cycle time, lead time for changes, deployment frequency, and change failure rates reflect efficiency and code reliability, while code quality, and technical debt help assess long-term maintainability.  “Tracking these metrics in conjunction with the business value being delivered ensures that productivity isn’t just about output, but about meaningful results that support organizational goals,” Franchetti says.   Related:Curtail Cloud Spend With These Strategies Garcia notes that qualitative measures such as developer satisfaction surveys and feedback sessions provide a human-centered view of productivity, highlighting areas that might need improvement in the workflow.   “In our work with clients, we’ve found that organizations that focus on both quantitative and qualitative measures, while fostering continuous feedback, consistently see higher productivity and engagement,” he says.   Enable Collaboration, Communication   Franchetti says it’s important to incorporate the development processes into modern collaboration tools. “With an increasingly dispersed workforce, it’s more essential than ever that these team-oriented tools become the backbone of the development process. If done well, these can be great productivity enablers.”  Steve Persch, director of developer relations at Pantheon, says that IT leaders should stay conscious of the analog predecessors of modern digital collaboration tools. “Chat tools like Slack can feel to any given employee like they are in countless, endless in-person meetings at once,” he cautions. “It’s bad for productivity and communication if everyone is constantly moving between tables of conversation.”  Instead, Persch suggests modern tools be paired with decidedly old-school conventions like weekly or monthly meetings in which decisions are made.  Related:Forrester Speaker Sneak Peek: Analyst Jayesh Chaurasia to Talk AI Data Readiness Helping Devs Attain Flow State   Developers reach “flow state” by immersing themselves in problem solving with code and technology during focused sessions with minimal interruption.  “Creating and fostering the kind of deep work sessions that lead to that flow state requires IT leaders to embrace a flexible work environment, flexible schedules, access to an effective set of tools that keeps developers within that state,” Garcia explains.   Most importantly, leaders should support and empower teams to experiment and iterate through new processes. Providing autonomy, setting clear goals, fostering open communication, and ensuring psychological safety for risk-taking without fear of failure are key to keeping developers focused and productive.  “Reducing external pressures, such as unnecessary meetings and administrative tasks, allows developers to maintain concentration and stay in the flow,” he says.   Persch says developers are more likely to stay in a flow state when they can easily see that the concerns beyond their work are getting handled.  Bug reports, stray product feedback, and other communication can come in through email, chat, and an uncountable number of other channels. “Rarely is the best option for a developer to break their focus and immediately jump on the new bug report,” he says.   Modes of Motivation   Franchetti says companies should foster a culture of continuous learning and experimentation to keep developers current and motivated, offering them flexible and personalized training paths.   Hands-on learning, mentorship programs, and cross-functional collaboration help solidify new skills, while knowledge-sharing sessions and dedicated time for both learning and experimentation encourage ongoing development.   “Supporting certifications, contributing to open-source projects, and ensuring access to modern tools can further enhance engagement,” he says. “Companies should also track and recognize upskilling achievements to boost motivation.”  Garcia thinks that leaders should promote a work culture that encourages regular breaks, flexible hours, and setting boundaries to avoid overwork. “By fostering an environment of psychological safety, where developers can freely express concerns or suggest improvements without fear of criticism, organizations can maintain a high level of engagement and creativity.”  source

“Is Your IT Service Desk Overwhelmed?“ Brought to you by TeamDynamix It is not hard for your IT Service Desk to become overwhelmed by the increasing demands of modern business environments. To address this challenge, it is essential to implement key strategies that can significantly reduce resource drain and improve efficiency. Below are actionable approaches designed to optimize your IT service operations: -Reduce Administrative Tasks: Streamlining these tasks through the use of effective management tools can save valuable time and effort, allowing your team to focus on more critical issues.  -Automate Manual Processes: Implementing automation for routine processes reduces the likelihood of errors and frees up resources, speeding up service delivery and enhancing accuracy.  -Improve Self-Service Adoption: Encouraging users to utilize self-service options can reduce the burden on your IT team. By offering comprehensive self-help resources and intuitive interfaces, users can resolve common issues independently and quickly. Deploying these methods empowers your IT service desk to not only meet current demands but also to maintain a sustainable performance level, preventing burnout and fostering a more resilient team environment. Offered Free by: TeamDynamix See All Resources from: TeamDynamix Thank you This download should complete shortly. If the resource doesn’t automatically download, please, click here. source

“The Ultimate Guide to Intelligent Document Processing“ Unlocking success with end-to-end automation: We’ll show you where to start with Intelligent Document Processing Enterprises run on documents and communications.Almost every process, in almost every department, needs a document or message to get the job done. Hiring and onboarding, accounts payable, sales and order management, customer service—the list goes on. The larger the organization, the more documents it needs to process and the more information it needs to extract. And, as every enterprise knows, managing it all can be a major financial and resource burden.   Combined in a single AI-powered IDP solution, UiPath IDP makes it simple to automate document-intensive processes, reduce manual paperwork, and increase operational efficiency right across the organization.  This paper provides a guide for enterprises looking to embrace the true potential of AI-powered IDP—discussing  where to start and how to succeed. Offered Free by: UiPath See All Resources from: UiPath source