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The board, formed in April, is made up of major software and hardware companies, critical infrastructure operators, public officials, the civil rights community, and academia, according to the release. A once in a generation opportunity Mayorkas explained the need for the framework in a report outlining the initiative, “AI is already altering the way Americans interface with critical infrastructure. New technology, for example, is helping to sort and distribute mail to American households, quickly detect earthquakes and predict aftershocks, and prevent blackouts and other electric-service interruptions. These uses do not come without risk, though: a false alert of an earthquake can create panic, and a vulnerability introduced by a new technology may risk exposing critical systems to nefarious actors.” AI, he said, offers “a once in-a-generation opportunity to improve the strength and resilience of US critical infrastructure, and we must seize it while minimizing its potential harms. The framework, if widely adopted, will go a long way to better ensure the safety and security of critical services that deliver clean water, consistent power, internet access, and more.” source

As organizations look to modernize IT systems, including the mainframe, there’s a critical need to do so without sacrificing security or falling out of compliance. But that’s a balancing act that is easier said than done, especially as cybersecurity threats grow increasingly sophisticated. Malicious actors have access to more tools and plans of attack than ever before. They’re also aggressive—in 2023 alone, there were more than 3,200 data compromises in the U.S. that affected over 350 million individuals. As those threats evolve, so too do the regulations and guidelines that are established in response. These shifts mean that companies have to prioritize a number of critical capabilities like annual or quarterly penetration testing, vulnerability scanning, audit logs, systematic access controls, and much more to remain compliant. Faced with this complex task, IT leaders need to ensure they are equipped to support new technologies while also adapting to an evolving regulatory and threat landscape if they are to keep modernization initiatives moving forward. Balancing modernization in a complex regulatory landscape Modernization is essential, and organizations that put off doing so risk getting left behind. Yet, one missed configuration-based vulnerability or data loss during a migration can be catastrophic. A single cybersecurity incident can ruin a company’s reputation with corporate partners and customers. And those incidents can have far-reaching consequences that go beyond the immediate damage to IT systems, data, or operations. But for mainframe systems, what can these incidents look like? Some of the most common mainframe vulnerabilities are: Code-based vulnerabilities. These vulnerabilities account for flaws in existing code (often from third parties) that can be exploited by cybercriminals. Configuration-based vulnerabilities. These vulnerabilities stem from improper settings and configurations that can leave systems open to unauthorized access. Insider threats. These threats represent employees or contractors who intentionally or unintentionally misuse their access to mainframe systems to harm an organization. Businesses will need to identify and implement the right strategy to combat those potential vulnerabilities while also accounting for a variety of new regulations, like the EU’s Digital Operational Resilience Act (DORA) or the Payment Card Industry Data Security Standard v4.0 (PCI DSS v4.0). More and updated localized cybersecurity regulations like 23 NYCRR Part 500, created by the New York State Department of Financial Services (NYDFS), require critical consideration, in this case requiring financial services companies operating in New York to conduct annual mainframe risk assessments, perform annual mainframe penetration testing, and have robust mainframe vulnerability management programs in place, to protect customer data and the systems they rely on. Policies and regulations like these make it more important than ever for organizations to catch vulnerabilities before they become full-fledged cyber attacks. Falling out of compliance could mean risking serious financial and regulatory penalties. With the stakes so high, IT leaders need to ensure their modernization strategies are inclusive of mainframe security.  The keys to mainframe security With the understanding that mainframe security is integral to broader modernization goals, where should organizations start? There are a few important elements that should make up an effective security strategy. Mainframe security requires a great deal of attention—threats and vulnerabilities are constantly evolving. To that end, one important step organizations can take to improve their mainframe security is to designate a mainframe security architect. This role can help design and maintain a secure environment that is tailored to the business’s specific needs while also helping to identify potential risks. From a practical standpoint, one of the more important aspects of new regulations, like DORA, is the role of regular testing and scanning for vulnerabilities. Every mainframe security strategy should incorporate capabilities like code-based vulnerability scanning, regular mainframe penetration testing, regular compliance checks, point-in-time data recovery, and widespread, fully deployed, multifactor authentication (MFA). That’s where working with a trusted partner with deep expertise in mainframe modernization and security can be a game-changer. Take, for example, the security solutions offered by Rocket Software, which deliver capabilities that are tailored to the complex security and regulatory realities facing mainframe systems. Tools like the Rocket z/Assure® Vulnerability Analysis Program automatically scan and pinpoint vulnerabilities in mainframe operating system code, making it easier to keep pace with potential threats as they evolve. Similarly, Rocket® Mainframe Security Services also offers a powerful solution for organizations looking to bolster their security with services like compliance assessments, penetration testing, and conversion services, among others. For modernization initiatives to be successful, businesses need to ensure they are prioritizing security and compliance as part of that journey. Mainframe systems bring with them a unique set of requirements, but by implementing the right programs, processes, and tools businesses can stay secure, minimize disruption, and adhere to local and international regulations. Learn more about how Rocket Software can support your modernization journey without sacrificing security or compliance. source

The CEO of Salesforce AI, Clara Shih, has left after just 20 months in the job. Neither Shih nor the company has made an official announcement, but a source familiar with the matter confirmed to CIO that Adam Evans, previously senior vice president of product for Salesforce AI Platform, has moved up to the newly created role of executive vice president and general manager of Salesforce AI. Evans has already updated his LinkedIn profile to reflect his new job title. In addition to corporate CEO Marc Benioff, Salesforce has a number of divisional or regional CEOs, of whom Shih was one. Some also hold the rank of executive vice president. source

As the new CDIO of Raychem RPG, what are your primary goals in the digital pursuits of the organization? What challenges do you foresee tackling in this role? Raychem RPG has a very progressive outlook on Digital and sees technology as a huge enabler for its business. A gradual and constant focus on integrating Digital into the business strategy remains our key focus to make these initiatives sustainable, and by weaving Digital into the cultural fabric of our organization, we continuously enable our workforce to become future ready. Being a manufacturing organization, industrial automation tech is at the heart of our digitization strategy – IOT, AI/ML, RPA, Robotics, intelligent automation, and eventually collating all data in a Data Warehouse to drive analytical insights. Liberating siloed data (SCADA, sensors, manual, satellite apps) and aggregating it with structured (ERP) data, and then creating a 360-degree view on almost anything – that is our holy grail. source

Not that long ago, database administrators (DBAs) were perceived as purely technical experts. While they played a critical enterprise role, it was primarily behind-the-scenes to ensure the integrity, security, and availability of the database. Today, DBAs are being pulled into the limelight. Corporate data is gold, and DBAs are its stewards. That’s reflected in employment statistics for database administrators and architects, positions projected to grow nine percent from 2023 to 2033, much faster than the average for all occupations.1 Data is likewise growing at an exponential rate. In fact, according to IDC, data creation and replication are experiencing a compound annual growth rate (CAGR) of 23% per year.2 As data volumes grow, so does corporate hunger to use it for broader business goals such as user experience design and insights for revenue generation. Complicating the issue is the fact that a majority of data (80% to 90%, according to multiple analyst estimates) is unstructured.3 Modern DBAs must now navigate a landscape where data resides across increasingly diverse environments, including relational databases, NoSQL, and data lakes. And they must work cross-functionally to facilitate data integration so the business can ultimately extract gold from all that data driving new business opportunities. But while DBAs have moved into a strategic advisory capacity, they’re not off the hook for all their other traditional responsibilities. If anything, it’s been an expansion, and now they must try to balance it all. So, the question becomes: how do enterprises help their DBAs unburden themselves so they can truly focus on strategy? The third-party effect One strategy is to work with a trusted third-party provider that can offer comprehensive support and expertise. Such a partner can help DBAs free themselves of traditional, time-consuming administrative activities and reinvest that time and their companies’ resources for broader business strategy.   Rimini Street, for example, has been providing enterprise software and database support for the past 20 years to thousands of enterprise customers. Rimini Support™ provides primary engineering support with 24/7 availability and average response times of under two minutes for critical P1 and P2 issues. Its accessibility at scale to support mission-critical operations removes costs and helps ease the burden on stretched resources. For iconic food manufacturer Welch’s, the move from vendor support for their Oracle Database to Rimini Street enabled their teams to reallocate their focus towards the creation of new application extensions for the business rather than working on troubleshooting. “Welch’s is a great example of a company that faced out-of-control maintenance costs, with forced upgrade pressures that offered no new features and functions to justify the trouble and expense,” says Robert Freeman, Rimini Street’s Oracle Enterprise Architect. “With Rimini Street, Welch’s immediately cut maintenance fees in half and their DBAs are no longer chasing trouble tickets, applying patches, or worrying about the risks associated with upgrades. They are now much more in control of their IT roadmap.” As DBAs continue to take on more of a consultative role within their organizations, they can benefit from third-party support solutions to bring efficiency to their day-to-day. Such solutions will enable them to move out of the daily grind and into the modern, multifaceted role companies need them to play.   Learn more about how Rimini Street enterprise software support services can help free critical time and resources for business-driven innovation. 1Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, Database Administrators and Architects 2Business Wire, “Data Creation and Replication Will Grow at a Faster Rate Than Installed Storage Capacity, According to the IDC Global DataSphere and StorageSphere Forecasts,” March 24, 2021 3MIT Sloan School of Management, “Tapping the power of unstructured data,” Feb 1, 2021 source

Layoffs and salary plateaus in the wake of exuberant pandemic-era IT hiring has the IT talent market in flux. And while employers pay premiums for hard-to-find AI skills, IT pros seek the same for filling in-office openings. source

By Bryan Kirschner, Vice President, Strategy at DataStax From the Wall Street Journal to the World Economic Forum, it seems like everyone is talking about the urgency of demonstrating ROI from generative AI (genAI). On the one hand, enthusiasm for getting out of “pilot purgatory” is a good sign. We know with the benefit of hindsight that under-investing in digital transformation meant leaving money on the table. And early evidence suggests that genAI has a lot to offer: Across five studies, its median impact on employee productivity was a 25% uplift. On the other hand, there are signals that some genAI critics are hellbent on persuading themselves that those results are too good to be true, And that’s likely to become a self-fulfilling prophecy, to their disadvantage. The risk is exemplified by the case of an executive canceling Microsoft Copilot subscriptions supposedly because “he compared the slide-generation capability of Microsoft’s AI tools to ‘middle school presentations.’” At least as it was reported, it comes across sounding like a flip dismissal of what genAI might have to offer. Contrast that with what I heard recently from a knowledge worker about how he uses genAI in his workflow. He leverages ChatGPT 4o to help generate prompts for Perplexity. He uses those prompts to elicit data from Perplexity that he then feeds back into prompts for ChatGPT. He did not get to the point of 100% specificity and confidence about exactly how this makes him happier and more productive through a quick one-and-done test of a use case or two. He got there as a result of willingness to test and learn, adopting a growth mindset, and management’s conviction that “where there’s a will, there’s a way” to put genAI to good use. If your organization is ambivalent about any of these things, you’re at risk of a genAI ROI doom loop, in which people may try very little and quickly run out of ideas. Committing to three principles sets the stage for people to take similarly mindful, holistic, and, in the end, high-ROI approaches to their own genAI journeys. These three best practices can help them on their way. Attack workflows, not just use cases Let’s assume for the sake of discussion that genAI currently does indeed stink at making PowerPoint presentations. That presentation in question sits inside two workflows. The first is substantive: It’s presumably being used in a meeting to inform some decision aimed at some outcomes. So one line of inquiry is “could we use genAI to achieve the same outcomes in a different way (up to and including without the presentation, the meeting. or the dreaded ‘meeting before the meeting’)?” The second is procedural: there are likely multiple people and steps involved in producing the presentation. So the line of inquiry here would be: “How might we use genAI to reduce time and toil or increase quality?”At least in the short term, genAI is unlikely to be a “magic bullet.” But to get down to brass tacks: successfully turning any meeting in the workflow into an email is a high-yield move. (In one study, employee productivity was 71% higher when meetings were reduced by 40%.) 2. Make ‘soft metrics’ matter Imagine an experienced manager with an “open door policy.” If you asked any more junior employee, they’d all say: “I always feel better about my next executive presentation if I run it by them first.” Or: “asking them to play ‘devil’s advocate’ always sharpens my thinking.” Now imagine telling them to end the open-door policy because it burns staff time and you don’t have hard numbers quantifying the ROI. Any established workflow probably has some cognitive load, stress, or procrastination embedded in it. It also probably has some unrealized potential for causing a feeling of accomplishment, a sense of teamwork, or new learning too. To be sure, the value of genAI must be articulable. But it would be an extreme case of old-school Taylorism to (for example) consider a team’s perspective flipping from “we dread preparing for business reviews” to “now we look forward to them as a time to shine” because the amount of prep time is still the same. 3. Think about ROI in terms of value proposition, not nickels and dimes Finally and most importantly: encourage every process, product, and experience owner to approach genAI as a way to rewrite the value proposition of their workflow. Each workflow is aimed at a problem or opportunity to be solved. The “competition” is the pre-genAI way of getting that done. Meaningful improvement is likely to include some quantifiable metrics like time savings or employee satisfaction. But the most powerful North Star is likely to be contextual and qualitative. Imagine a team that shifts from “feeling beleaguered” to “feeling like rock stars.” Or whose stakeholders move from saying they’re “hit or miss” at delivering on time to “they’re totally reliable.” And as an added bonus: if teams literally write down how they’re using genAI and its impact (both qualitative and quantitative), that’s a great retrieval-augmented generation (RAG) use case. GenAI itself can report week-on-week progress, putting it to work across your organization–including the ROI. It’s all the more reason that a great starting point for demonstrating immediate and meaningful value is getting the people who are already involved in each of those activities engaged in putting it to good use and sharing what they’ve learned. Learn how DataStax enables enterprises and developers to get GenAI apps to production fast. About Bryan Kirschner:Bryan is Vice President, Strategy at DataStax. For more than 20 years he has helped large organizations build and execute strategy when they are seeking new ways forward and a future materially different from their past. He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing. source