Quote for the day:
“If you don’t have a competitive advantage, don’t compete.” -- Jack Welch
Security Is Blocking AI Adoption: Is BYOC the Answer?
Enterprises face unique hurdles in adopting AI at scale. Sensitive data must
remain within secure, controlled environments, avoiding public networks or
shared infrastructures. Traditional SaaS models often fail to meet these
stringent data sovereignty and compliance demands. Beyond this, organizations
require granular control, comprehensive auditing and full transparency to trace
every AI decision and data access. This ensures vendors cannot interact with
sensitive data without explicit approval and documentation. These unmet needs
create a significant gap, preventing regulated industries from deploying AI
solutions while maintaining compliance and security. ... The concept of Bring
Your Own Cloud (BYOC) isn’t new. It emerged as a middle ground between
traditional SaaS and on-premises deployments, promising to combine the best of
both worlds: the convenience of managed services with the control and security
of on-premises infrastructure. However, its history in the industry has been
marked by both successes and cautionary tales. Early BYOC implementations often
failed to live up to their promises. Some vendors merely deployed their software
into customer cloud accounts without proper architectural planning, resulting in
what was essentially remotely managed on-premises environments.
The Importance of Continuing Education in Data and Tech
Continuing education plays a vital role in workforce development and career
advancement within the tech industries, where rapid technological advancements
and evolving market demands necessitate a culture of lifelong learning. As
businesses increasingly rely on sophisticated data analytics, artificial
intelligence (AI), and cloud technologies, professionals in these fields must
continuously update their skills to remain competitive. Continuing education
offers a pathway for individuals to acquire new capabilities, adapt to emerging
technologies, and gain proficiency in specialized areas that are in high demand.
By engaging in ongoing learning opportunities, tech professionals can enhance
their expertise, making them more valuable to their current employers and more
attractive to potential future ones. ... Professional certifications and
competency-based education have become significant avenues for career
advancement in the data and tech field. As the landscape of technology rapidly
evolves, organizations increasingly seek professionals who possess validated
skills and up-to-date knowledge. Professional certifications serve as tangible
proof of one’s expertise in specific areas such as data governance, analytics,
cybersecurity, or cloud computing. These certifications, offered by leading
industry bodies and tech companies, are designed to align with current industry
standards and demands.
Agents, shadow AI and AI factories: Making sense of it all in 2025
“Agentic AI” promises “digital agents” that learn from us, and can perceive,
reason problems out in multiple steps and then make autonomous decisions on our
behalf. They can solve multilayered questions that require them to interact with
many other agents, formulate answers and take actions. Consider forecasting
agents in the supply chain predicting customer needs by engaging customer
service agents, and then proactively adjusting warehouse stock by engaging
inventory agents. Every knowledge worker will find themselves gaining these
superhuman capabilities backed by a team of domain-specific task agent workers
helping them tackle large complex jobs with less expended effort. ... However,
the proliferation of generative, and soon agentic AI, presents a growing problem
for IT teams. Maybe you’re familiar with “shadow IT,” where individual
departments or users procure their own resources, without IT knowing. In today’s
world we have “shadow AI,” and it’s hitting businesses on two fronts. ...
Today’s enterprises create value through insights and answers driven by
intelligence, setting them apart from their competitors. Just as past industrial
revolutions transformed industries — think about steam, electricity, internet
and later computer software — the age of AI heralds a new era where the
production of intelligence is the core engine of every business.
Is VMware really becoming the new mainframe?
“CIOs can start to unwind their dependence on VMware,” he says. “But they need
to know it may not have any material reduction in their spend with Broadcom over
multiple renewals. They’re going to have to get completely off Broadcom.” Still,
Warrilow recommends that CIOs running VMware consider alternatives over the long
term. They should also look for exit strategies for other market-dominant IT
products they use, given that Broadcom has seen early success with VMware, he
says. “The cautionary tale for CIOs is that this is just the beginning,” he
says. “Every tech investment firm is going to be saying, ‘I want what Broadcom
has with their share price.’ ... “The comparison works a bit, maybe from a
stickiness perspective, because customers have built their applications and
workload using virtualization technology on VMware,” he says. “When they have to
do a mass refactoring of applications, it’s very, very hard.” But the analogy
has its limitations because many users think of mainframes as a legacy
technology, while VMware’s cloud-based products address future challenges, he
adds. “The cloud is the future for running your AI workload,” Shenoy says.
“Customers have trusted us for the last 20 to 25 years to run their
business-critical applications, and the interesting part right now is we are
seeing a lot of growth of these AI workloads and container workloads running on
VMware.”
Deep Learning – a Necessity
It is essential in architecture that we realize that a skill set is not an
arbitrary thing. It isn’t learn one skill and you are done. It also isn’t learn
any skill from any background and you’re in. It is the application of all of the
identified and necessary skills combined that makes a distinguished architect.
It is also important to understand the purpose and context of mastery. Working
in a startup is very different from working in a large corporation. Industry can
change things significantly as well. Always remember that the profession’s
purpose has to be paramount in the learning. For example, both doctors and
lawyers have to deal with clients and need human interaction skills to be
successful. Yet, the nature and implementation of these differ drastically. We
will explore this point in a further article. However, do not underestimate the
impact of changing the meaning of the profession while claiming similar skills.
The current environment is rife with this kind of co-opting of the terminology
and tools to alter the whole purpose of architecture fundamentally. ... In
medicine and other professions, an individual studies and practices for 7+ years
to become fully independent, and they never stop learning. This learning is
tracked by both mentors and the profession. Because medicine is so essential to
humans it is important that professionals are measured and constantly update and
hone their competencies.
Crawl, then walk, before you run with AI agents, experts recommend
The best bet for percolating AI agents throughout the organization is to keep
things as simple as possible. "Companies and employees that have already found
ways to operationalize intelligent agents for simple tasks are best placed to
exploit the next wave with agentic AI," said Benjamin Lee, professor of computer
and information science at the University of Pennsylvania. "These employees
would already be engaging generative AI for simple tasks and they would be
manually breaking complex tasks into simpler tasks for the AI. Such employees
would already be seeing productivity gains from using generative AI for these
simple tasks." Rowan agreed that enterprises should adopt a crawl, walk, run
approach: "Begin with a pilot program to explore the potential of multiagent
systems in a controlled, measurable environment." "Most people say AI is at the
toddler stage, whereas agentic AI is like a tween," said Ben Sapp, global
practice lead of intelligence at Digital.ai. "It's functional and knows how to
execute certain functions." Enterprises and their technology teams "should
socialize the use of generative AI for simple tasks within their organizations,"
Lee continued. "They should have strategies for breaking complex tasks into
simpler ones so that, when intelligent agents become a reality, the sources of
productivity gains are transparent, easily understood, and trusted."
Growth of digital wallet use shaking up payment regulations and benefits delivery
Australian banks are calling on the government to pass legislation that
accommodates payments with digital wallets within the country’s regulatory
framework. A release from the Australian Banking Association (ABA) argues that
with the country’s residents making $20 billion worth of payments across 500
million transactions each month with mobile wallets, all players within the
payment ecosystem should be under the remit of the Reserve Bank of Australia.
... Digital wallets are by far the most popular method of making cross-border
payments, according to a new report from Payments Cards & Mobile. The How
Digital Wallets Are Transforming Cross-Border Transactions report shows digital
wallets are chosen for international transactions by 42.1 percent. That makes
them more people than the next two most popular methods, money transfer services
(16.8 percent) and bank accounts (14.8 percent) combined. Transactions with
digital wallets are much faster than wire transfers, are available to people who
don’t possess bank accounts, and have lower fees than bank transfers, the report
says. Interoperability remains a challenge, and regulations and infrastructure
limitations could pose barriers to adoption, but the report authors only expect
the dominance of digital wallets to increase in the years ahead.
My vision is to create a digital twin of our entire operations, from design and manufacturing to products and customers
We approach this transformation from three dimensions. First is empathy – truly
understanding not just who our customers are, but their emotions. This is where
the concept of creating a ‘digital twin’ of the customer comes in. Second is
innovation – not just adopting new technologies but ensuring that our processes
are lean, digitised, and seamless throughout the customer journey, from research
to purchase, service, and brand loyalty. The goal is to provide a consistent and
empathetic experience across all touchpoints. ... The first challenge is
identifying our customers. For example, if a distributor in one business also
buys from another or if a consumer connects with one of our industrial projects,
it’s hard to track. To address this, we launched a customer UID project, which
has been in progress for months. It helps us identify customers across channels
while keeping an eye on privacy and adhering to upcoming data protection
regulations. The second part involves gathering all customer-related data in one
place. Over the past three years, we unified all customer interactions into a
single platform with a one CRM strategy, which was complex but essential. Now,
with AI solutions like social listening combined with sentiment analysis, we can
understand what our customers are saying about us and where we need to improve,
both in India and globally.
Will AI Chip Supply Dry Up and Turn Your Project Into a Costly Monster?
CIOs and other IT leaders face tremendous pressure to quickly develop GenAI
strategies in the face of a potential supply shortage. With the cost of
individual units, spending can easily reach into the multi-million-dollar range.
But it wouldn’t be the first time companies have dealt with semiconductor
shortages. During the COVID-19 pandemic, a spike in PC demand for remote work
met with global shipping disruptions to create a chip drought that impacted
everything from refrigerators to automobiles and PCs. “One thing we learned was
the importance of supply chain resiliency, not being overly dependent on any one
supplier and understanding what your alternatives are,” Hoecker says. “When we
work with clients to make sure they have a more resilient supply chain, we
consider a few things … One is making sure they rethink how much inventory do
they want to keep for their most critical components so they can survive any
potential shocks.” She adds, “Another is geographic resiliency, or understanding
where your components come from and do you feel like you’re overly exposed to
any one supplier or any one geography.” Nvidia’s GPUs, she notes, are harder to
find alternatives for -- but other chips do have alternatives. “There are other
places where you can dual-source or find more resiliency in your marketplace.”
WTF? Why the cybersecurity sector is overrun with acronyms
Imagine an organization is in the midst of a massive hack or security breach,
and employees or clients are having to Google frantically to translate company
emails, memos or crisis plans, slowing down the response. When these acronyms
inevitably migrate into a cybersecurity company’s external marketing or
communications efforts, they’re almost guaranteed to cause the general public to
tune out news about issues and innovations that could have a far-reaching impact
on how people live their lives and conduct their businesses. This is especially
true as artificial intelligence (AI!) and machine learning (ML!) technologies
expand and new acronyms emerge to keep pace with developments. Acronyms can also
have unfortunate real-life connotations — point of sale, to name just one
example. When shortened to POS, it can suggest something is… well, crappy. ...
So, what’s behind the tendency to shorten terms to a jumble of often
incomprehensible acronyms and abbreviations? “On the one hand, acronyms,
abbreviations and jargon are used to achieve brevity, standardization and
efficiency in communication, so if a profession is steeped in complex and
technical language, it will likely be flowing with acronyms,” says Ian P.
McCarthy, a professor of innovation and operations management at Simon Fraser
University in Burnaby, British Columbia.
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