Executive Q&A: Data Quality, Trust, and AI
Data observability is the process of interrogating data as it flows through a
marketing stack -- including data used to drive an AI process. Data
observability provides crucial visibility that helps users both interrogate data
quality and understand the level of data quality prior to building an audience
or executing a campaign. Data observability is traditionally done through visual
tools such as charts, graphs, and Venn diagrams, but is itself becoming
AI-driven, with some marketers using natural language processing and LLMs to
directly interrogate the data used to fuel AI processes. ... In a way, data
silos are as much a source of great distress to AI as they are to the customer
experience itself. A marketer might, for example, use a LLM to help generate
amazing email subject lines, but if AI generates those subject lines knowing
only what is happening in that one channel, it is limited by not having a
360-degree view of the customer. Each system might have its own concept of a
customer’s identity by virtue of collecting, storing, and using different
customer signals. When siloed data is updated on different cycles, marketers
lose the ability to engage with a customer in the precise cadence of the
customer because the silos are out of synch with a customer journey.
Only 10% of Organizations are Doing Full Observability. Can Generative AI Move the Needle?
The potential applications of Generative AI in observability are vast. Engineers
could start their week by querying their AI assistant about the weekend’s system
performance, receiving a concise report that highlights only the most pertinent
information. This assistant could provide real-time updates on system latency or
deliver insights into user engagement for a gaming company, segmented by
geography and time. Imagine being able to enjoy your weekend and arrive at work
with a calm and optimistic outlook on Monday morning, and essentially saying to
your AI assistant: “Good morning! How did things go this weekend?” or “What’s my
latency doing right now, as opposed to before the version release?” or “Can you
tell me if there have been any changes in my audience, region by region, for the
past 24 hours?” These interactions exemplify how Generative AI can facilitate a
more conversational and intuitive approach to managing development
infrastructure. It’s about shifting from sifting through data to engaging in
meaningful dialogue with data, where follow-up questions and deeper insights are
just a query away.
The Ultimate Roadmap to Modernizing Legacy Applications
IT leaders say they plan to spend 42 percent more on average on application
modernization because it is seen as a solution to technical debt and a way for
businesses to reach their digital transformation goals, according to the 2023
Gartner CIO Agenda. But even with that budget allocated, businesses still face
significant challenges, such as cost constraints, a shortage of staff with
appropriate technical expertise, and insufficient change management policies to
unite people, processes and culture around new software. To successfully
navigate the path forward, IT leaders need a strategic roadmap for application
modernization. The plan should include prioritizing which apps to upgrade,
aligning the effort with business objectives, getting stakeholder buy-in,
mapping dependencies, creating data migration checklists and working with
trusted partners to get the job done. ... “Even a minor change to the
functionality of a core system can have major downstream effects, and failing to
account for any dependencies on legacy apps slated for modernization can lead to
system outages and business interruptions,” Hitachi Solutions notes in a
post.
Is it time to split the CISO role?
In one possible arrangement, a CISO reports to the CEO and a chief security
technology officer (CSTO), or technology-oriented security person, reports to
the CIO. At a functional level, putting the CSTO within IT gives the CIO a
chance to do more integration and collaboration and unites observability and
security monitoring. At the executive level, there’s a need to understand
security vulnerabilities and the CISO could assist with strategic business risk
considerations, according to Oltsik. “This kind of split could bring better
security oversight and more established security cultures in large
organizations.” ... To successfully change focus, CISOs would need to get a
handle on things like the financials and company strategy and articulate cyber
controls in this framework, instead of showing up every quarter with reports and
warnings. “CISOs will need to incorporate their risk taxonomy into the overall
enterprise risk taxonomy,” Joshi says. In this arrangement, however, the budget
could arise as a point of contention. CIO budgets tend to be very cyber heavy
these days, Joshi explains, and it could be difficult to create the situation
where both the CISO and CIO are peers without impacting this allocation of
funds.
Empowering IIoT Transformation through Leadership Support
To gain project acceptance and ultimately ensure project success will rely
heavily on identifying all key stakeholders, nurturing an on-going level of
mutual trust and maintaining a strong focus on targeted end results. This
involves a full disclosure of desired outcomes and a willingness to adapt to
individual departmental nuances. Begin with a cross-department
kickoff/planning meeting to identify interested parties, open projects, and
available resources. Invite participation through a discovery meeting,
focusing on establishing the core team, primary department, cross-department
dependencies, and consolidating open projects or shareable resources. ...
Identifying all digital data blind spots at the outset highlights the scale of
the problem. While many companies have Artificial Intelligence (AI) and
Business Intelligence (BI) initiatives, their success depends on the quality
of the source data. Consolidating these initiatives to address digital data
blind spots strengthens the data-driven business case. Once a critical mass of
baselines is established, projecting Return On Investment (ROI) from both a
quantification and qualification perspective becomes possible.
Will more AI mean more cyberattacks?
Organisations are also potentially exposing themselves to cyber threats
through their own use of AI. According to research by law firm Hogan Lovells,
56 per cent of compliance leaders and C-suite executives believe misuse of
generative AI within their organisation is a top technology-associated risk
that could impact their organisation over the next few years. Despite this,
over three-quarters (78 per cent) of leaders say their organisation allows
employees to use generative AI in their daily work. One of the biggest threats
here is so-called ‘shadow AI’, where criminals or other actors make use of, or
manipulate, AI-based programmes to cause harm. “One of the key risks lies in
the potential for adversaries to manipulate the underlying code and data used
to develop these AI systems, leading to the production of incorrect, biased or
even offensive outcomes,” says Isa Goksu, UK and Ireland chief technology
officer at Globant. “A prime example of this is the danger of prompt injection
attacks. Adversaries can carefully craft input prompts designed to bypass the
model’s intended functionality and trigger the generation of harmful or
undesirable content.” Jow believes organisations need to wake up to the risk
of such activities.
What It Takes to Meet Modern Digital Infrastructure Demands and Prepare for Any IT Disaster
As you evaluate the evolving needs of your organization’s own infrastructure
demands, consider whether your network is equipped to handle a growing volume
of data-intensive applications — and if your team is ready to act in the face
of unexpected service interruption. The push to adopt advanced technologies
like AI and automation are the main drivers of network optimization for most
organizations. But the growing prevalence of volatile, uncertain, complex, and
ambiguous (VUCA) situations is another reason to review your communications
infrastructure’s readiness to withstand future challenges. VUCA is a catch-all
term for a wide range of unpredictable and challenging situations that can
impact an organization’s operations, from natural disasters to political
conflict, economic instability, or cyber-attacks. ... Maintaining operational
continuity and resilience in the face of VUCA events requires a combination of
strategic planning, operational flexibility, technological innovation, and
risk-management practices. This includes investing in technology that improves
agility and resilience as well as in people who are prepared for adaptive
decision-making when VUCA situations arise.
APIs Are the Building Blocks of Bank Innovation. But They Have a Risky Dark Side
A key point is that it’s not just institutions suffering. Frequently APIs used
by banks draw on PII (personally identifiable information) such as social
security numbers, driver’s license data, medical information and personal
financial data. APIs may also handle device and location data. “While this
data may not seem as sensitive as PII or payment card details at first glance,
it can still be exploited by malicious actors to gain insights into a user’s
behavior, preferences and movements,” the report says. “In the wrong hands,
this information could be used for targeted phishing attacks, social
engineering, or even physical threats.” “Everything in the financial
transaction world today is going across the internet, via APIs,” says Bird.
... Bird points out that the bad guys have more than just tools from the dark
web to help them do their business. Frequently they tap the same mainstream
tools that bankers would use. He laughs when he recalls demonstrating to a
reporter how a particular fraud would have been assisted using Excel pivot
tables. The journalist didn’t think of criminals using legitimate software.
“Why wouldn’t they?” said Bird.
Enterprise AI Requires a Lean, Mean Data Machine
Today’s LLMs need volume, velocity, and variety of data at a rate not seen
before, and that creates complexity. It’s not possible to store the kind of
data LLMs require on cache memory. High IOPS and high throughput storage
systems that can scale for massive datasets are a required substratum for LLMs
where millions of nodes are needed. With superpower GPUs capable of
lightning-fast read storage read times, an enterprise must have a low-latency,
massively parallel system that avoids bottlenecks and is designed for this
kind of rigor. ... It’s crucial that these technological underpinnings of the
AI era be built with cost efficiency and reduction of carbon footprint in
mind. We know that training LLMs and the expansion of generative AI across
industries are ramping up our carbon footprint at a time when the world
desperately needs to reduce it. We know too that CIOs consistently name
cost-cutting as a top priority. Pursuing a hybrid approach to data
infrastructure helps ensure that enterprises have the flexibility to choose
what works best for their particular requirements and what is most
cost-effective to meet those needs.
Building Resilient Security Systems: Composable Security
The concept of composable security represents a shift in the approach to
cybersecurity. It involves the integration of cybersecurity controls into
architectural patterns, which are then implemented at a modular level. Instead
of using multiple standalone security tools or technologies, composable
security focuses on integrating these components to work in harmony. ... The
concept of resilience in composable security is reflected in a system's
ability to withstand and adapt to disruptions, maintain stability, and
persevere over time. In the context of microservices architecture, individual
services operate autonomously and communicate through APIs. This design
ensures that if one service is compromised, it does not impact other services
or the entire security system. By separating security systems, the impact of a
failure in one system unit is contained, preventing it from affecting the
entire system. Furthermore, composable systems can automatically scale
according to workload, effectively managing increased traffic and addressing
new security requirements.
Quote for the day:
"The task of leadership is not to put
greatness into humanity, but to elicit it, for the greatness is already
there." -- John Buchan
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