GenAI surges in law firms: Will it spell the end of the billable hour?
All areas of law will use genAI, according to Joshua Lenon, Clio’s Lawyer in
Residence. That’s because AI content generation and task automation tools can
help the business side and practice efforts of law firms. However, areas that
have repetitive workflows and large document volumes – like civil litigation –
will adopt genAI e-discovery tools more quickly. Practice areas that charge
exclusively flat fees – like traffic offenses and immigration – are already the
largest adopters of genAi. ... Nearly three-quarters of a law firm’s hourly
billable tasks are exposed to AI automation, with 81% of legal secretaries’ and
administrative assistants’ tasks being automatable, compared to 57% of lawyers’
tasks, according a survey of both legal professionals (1,028) and another adults
(1,003) in the U.S. general population, by Clio. Hourly billing has long been
the preference of many professionals, from lawyers to consultants, but AI
adoption is upending this model where clients are charged for the time spent on
services. ... People have been talking about the demise of the billable hour for
about 30 years “and nothing’s killed it yet,” said Ryan O’Leary, research
director for privacy and legal technology at IDC. “But if anything will, it’ll
be this.”IT security and government services: Balancing transparency and security
For cyber defenses, government IT leaders should invest in website hosting
services with Secure Sockets Layer (SSL) encryption, and further enhancing
security with HTTP Strict Transport Security (HSTS). These measures ensure that
all data exchanged via government sites is encrypted, protecting resident
self-service features such as online voter registration, permit submissions,
utility bill payments, and more. By enforcing HSTS, websites are also protected
from protocol downgrade attacks and cookie hijacking, ensuring that all
connections remain secure, and reducing the risk of data interception. Other
marks of a reliable website hosting solution provider include DDoS mitigation
coverage and reliability around regular software patching and updates. For all
digital partners, it’s essential to consider third-party risk. Some of the most
valuable information residents should be able to access – meeting minutes,
agendas, and other documents pertaining to local governing decisions – are
hosted by document management vendors. To ensure this access is secure, each
vendor must be vetted on its security capabilities, so that critical data is
always protected, and hackers are not able to prevent access for residents or
laterally move further into government networks.Software buying trends are changing: From SaaS to outcome as a service
The last decade saw the rise of Software-as-a-Service (SaaS), transforming how
businesses approached software deployment. This decade belongs to
Outcomes-as-a-Service. CIOs are no longer interested in building large internal
developer teams or experimenting with different platforms. They seek business
impacting solutions with tangible outcomes that drive business success. Business
teams need solutions that deliver results today, not tomorrow. ... AI-powered
hyperautomation combines generative AI, BPM, RPA, integrations, analytics, and
app-building to drive end-to-end outcomes. In today’s dynamic business
environment, an integrated approach is essential. Siloed automation with
narrowly focused platforms is no longer sufficient. ... AI-platforms excel in
delivering outcomes at speed and scale. Leveraging automation expertise, they
ensure outcomes linked to growth, efficiency, and compliance. The platform
implements continuous cycles of process mining, implementation, adoption, and
solution refinement until desired objectives are met.They also offer a
comprehensive solution, managing everything from process definition and
refinement to platform implementation, support, application development, and
adoption. How Retailers Are Using Tech for Competitive Advantage
“While technology can streamline operations, an overreliance on automation
without human touch can sometimes backfire,” Peters says. “Consumers still value
human interaction, especially in complex support scenarios. It’s crucial for
retailers to balance automation with human agents, particularly in areas that
require empathy and nuanced decision-making.” ... Companies of all sizes benefit
from greater organizational efficiency, and tech has been the fuel powering
digital transformation. For example, Lowes uses AR for home improvement shopping
while Sephora uses it for virtual make up try-ons. Walmart is stepping up
automation in its battle against Amazon. But smaller retailers are benefiting,
too. ... “One of our customer’s last large-scale automation took them five
years from the time they started the concept to deployment,” Naslund says. “For
context, the pandemic, was four and a half years, and the amount of volatility
that the supply chain saw over the four years was insane. We saw inventory
gluts, inventory shortages, and panic buying. Then you saw a warehouse shortage
capacity, everybody's panicking to get warehouses. Then, they suddenly have too
much space.” Why and How IT Leaders Can Embrace the AI Revolution
AI software certainly has some consequences for IT departments. There may be
some new types of workflows to manage, new user requests to support, and new
application deployments to track. But unless your business is actually building
complex AI solutions from scratch — which it probably isn't or shouldn't because
sophisticated, mature AI tools and services are available from external vendors,
complete with support plans and SLAs — implementing AI is not actually that
challenging. That's because most third-party AI solutions boil down to SaaS apps
that work just like any other SaaS: The vendor builds, manages, and supports
them, with few resources and little effort necessary on the part of customers'
IT departments. From the perspective of IT, implementing AI isn't all that
different from implementing any other type of software. ... For IT, there are
really not any novel data privacy or security risks at stake here. The app
ingests financial data, but so do plenty of non-AI applications. IT's
responsibility when it comes to managing data security for this type of app
boils down to vetting the vendor by reviewing its data management and compliance
practices. The fact that the app uses AI doesn't change this process.Has the time come for integrated network and security platforms?
Interest in platformization is growing among enterprises, asserts Extreme
Networks, which recently surveyed 200 CIOs and senior IT leaders for its
research, CIO Insights Report: Priorities and Investment Plans in the Era of
Platformization. ... A platform that helps organizations transition their
network to the cloud to streamline IT efficiency and lower total cost of
ownership is important, respondents said. In addition, 55% of respondents
emphasized the need to integrate from a broad ecosystem of networking and
security offerings, indicating a clear demand for unified platforms, Extreme
concluded. ... “The message I got from the survey was that customers are
operating in a world where there’s a massive proliferation of products, or
applications, and that’s really translating into complexity. Complexity is equal
to risk, and that complexity is happening in multiple places,” said Extreme
Networks CTO Nabil Bukhari. Complexity is an interesting topic because it
changes, Bukhari said. The first Ford cars were basically just an engine with
brakes, but they were complicated to start and drive. “Now, if you look at a
car, they are like data centers on wheels. But driving and owning them is
exponentially easier,” Bukhari said.How legacy IT systems can hold your business back
While legacy IT systems may still be functional, they can hold a business back
from reaching its full potential – especially if market competitors are busy
upgrading their own systems. Companies need to carefully evaluate the costs
and benefits of keeping legacy systems in place and develop a plan to
modernize their IT infrastructure. Investing in a modern data center solution
can, over time, improve business agility, security, and your organization’s
bottom line. ... This is especially true when it comes to next-generation
applications using LLMs and machine learning (ML) for AI-dependent
applications. Enterprise servers, storage and networking hardware, and
software manufactured before about 2016 were not designed with scaled-up data
workloads in mind – especially workloads for genAI, which just started to take
off in 2021. This can hinder growth and force companies to invest in
additional hardware or software just to maintain their current operations.
Legacy systems are also more prone to failures and outages due to aging
hardware and software. This downtime disrupts operations and leads to lost
revenue, especially for critical business functions. Additionally, data loss
from system crashes can be costly to recover from.Architecture Inversion: Scale by Moving Computation, Not Data
Now why should the rest of us care, blessed as we are with a lack of most of
the billions of users TikTok, Google and the likes are burdened with? A number
of factors are becoming relevant:ML algorithms are improving and so is local
compute capacity, meaning fully scoring items gives a larger boost in quality
and ultimately profit than used to be the case. With the advent of vector
embeddings, the signals consumed by such algorithms have grown by one to two
orders of magnitude, making the network bottleneck more severe. Applying ever
more data to solve problems is increasingly cost effective, which means more
data needs to be rescored to maintain a constant quality loss. As the
consumers of data from such systems move from being mostly humans to mostly
LLMs in RAG solutions, it becomes beneficial to deliver larger amounts of
scored data faster in more applications than before. ... For these reasons,
the scaling tricks of the very biggest players are becoming increasingly
relevant for the rest of us, which has led to the current proliferation of
architecture inversion, going from traditional two-tier systems where data is
looked up from a search engine or database and sent to a stateless compute
tier to inserting that compute into the data itself.The secret to successful digital initiatives is pretty simple, according to Gartner
As with all technologies, seeing results from AI comes down to focusing like a
laser beam on the problem at hand: "In my experience, the businesses that
start with a real use case and problem are seeing an ROI," Julian LaNeve,
chief technology officer at Astronomer, a data platform company, told ZDNET.
"They define a well-scoped, impactful problem and use gen AI to solve [it],
and it's easy to measure success and ROI. The most successful business cases
identify how to solve a problem that the business already cares deeply about
and [will] deliver additional value to customers." Technology maturity also
makes a difference in success rates. "Previous generations of AI were narrower
in scope but have been successful," said Dominic Sartorio, vice president at
Denodo, a data management provider. "AI is helping with predictive maintenance
of manufactured goods, predicting demand spikes in [the] markets, and finding
the optimal routes for logistics, and [has] been successful for many years."
Furthermore, according to Gartner, companies that treat their digital
initiatives in a collaborative fashion -- between business and IT leaders --
rather than leaving all things digital up to their IT departments are
successful with technology. Showing AI users diversity in training data can boost perceived fairness and trust
The work investigated whether displaying racial diversity cues—the visual
signals on AI interfaces that communicate the racial composition of the
training data and the backgrounds of the typically crowd-sourced workers who
labeled it—can enhance users' expectations of algorithmic fairness and trust.
Their findings were recently published in the journal Human-Computer
Interaction. AI training data is often systematically biased in terms of race,
gender and other characteristics, according to S. Shyam Sundar, Evan Pugh
University Professor and director of the Center for Socially Responsible
Artificial Intelligence at Penn State. "Users may not realize that they could
be perpetuating biased human decision-making by using certain AI systems," he
said. Lead author Cheng "Chris" Chen, assistant professor of communication
design at Elon University, who earned her doctorate in mass communications
from Penn State, explained that users are often unable to evaluate biases
embedded in the AI systems because they don't have information about the
training data or the trainers. "This bias presents itself after the user has
completed their task, meaning the harm has already been inflicted, so users
don't have enough information to decide if they trust the AI before they use
it," Chen saidQuote for the day:
"It takes courage and maturity to know the difference between a hoping and a wishing." -- Rashida Jourdain
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