Maybe it was all a parable.
Technology is advancing rapidly, and one of the groundbreaking
breakthroughs in recent times is Generative Artificial Intelligence (AI).
Generative AI has revolutionized the way we approach creativity and
problem-solving in various domains. In this article, I will explore the
potential of generative AI and its implications across industries from my
perspective. From my previous articles we can see how the right tool in the
right place can produce the right results. I spoke earlier of data growth and accessibility
is facilitating the rapid growth of AI services. Gartner predicts “By 2025,
generative AI will be producing 10 percent of all data (now it’s less than 1
percent) with 20 percent of all test data for consumer-facing use cases.” So
not only do we have vast amounts of data to fuel AI, but it in itself is also
producing data.
What is Generative AI?
Generative AI refers to the ability of AI models to create content,
such as images, music, or text, that is completely original and
indistinguishable from human-created content. Unlike traditional AI models that
rely on predefined rules and patterns, generative AI learns from vast amounts
of data and creatively generates new content.
The Power of Creativity:
Generative AI has introduced a new realm of creativity by
expanding the boundaries of what can be imagined and produced. With generative
AI, content creators can leverage AI models to generate original artwork, music
compositions, or even entire stories. This empowers artists, musicians, and
writers to explore new avenues of expression and innovation. In my business this
creativity goes one step further. GitHub Copilot for examples extends script
creation by developers to match style and context while adding efficiency to
coding in many languages. Microsoft 365 Copilot can be used to extend content
creation into business documents like Excel, Word, Loop and PowerPoint or
directly into Outlook. "Can you make a SWOT?" or “Can you make a Chart from X notes…”
Enhanced Product Design:
Generative AI has proved to be a game-changer in product
design by assisting designers in generating innovative and personalized
solutions. By leveraging generative AI, designers can quickly generate and
iterate through design alternatives, saving time and resources. This allows for
the creation of more unique and tailored products, meeting various consumer
preferences. This can apply in any industry for functional group. I focus on information
Technology, but I can storyboard multiple choices for my children’s books. I
can also use it for IT architectural alternatives. Gartner predicts that “By
2027, 30 percent of manufacturers will use generative AI to enhance their
product development effectiveness.” Just a few examples of how a “product” can
be anything you chose, and AI can drive value into that product or its delivery
stream.
Evolution of Marketing:
Generative AI has transformed marketing strategies by enabling
businesses to create more engaging and personalized campaigns. AI models can
analyze vast amounts of consumer data to generate targeted ads that appeal to
specific demographics. This level of personalization enhances user experience
and drives better customer engagement. You see it everyday with Facebook and
Instagram driving focused marketing advertising based on history. Sometimes it’s
accuracy is scary, and no, “you don’t need to order that”. There are lots of
articles on how recommendation engines drive impulse buying. Those are enhanced
by AI as well.
Generative AI has added value regarding people management
while walking a thin ethical line. It can provide current employee assessments,
training recommendations, career path evaluation as well as streamline the
onboarding process to weed through the application and interview process. It is
used on both sides of the hiring process. You can have AI write a resume, cater
a cover letter, or simply adjust the tone or formality of a document.
Advancements in Healthcare:
Generative AI has immense potential in healthcare. From
diagnosis to treatment, AI models can generate insights and recommendations to
assist healthcare professionals. By analyzing extensive medical records and
data, generative AI can predict disease outcomes, recommend personalized
treatment plans, and even facilitate drug discovery. Johnson and Johnson had recently
quoted “AI is not only helping us identify the right targets for complex
diseases, but it's also helping us design fit-for-purpose molecules to treat
diseases and optimize them to provide targeted treatment to the disease while
also reducing the impact of side effects." Imagine what the future holds
as targeted datasets for AI are pretrained into GANs and take us to the next
level of disease discovery, control, and treatment. I can’t wait to see what AI
brings when I’m 150 years old.
Advancements in Security:
Security is paramount in IT operations. Generative AI can
analyze network traffic patterns and identify potential security threats,
including zero-day vulnerabilities and malicious activities. This proactive
approach to cybersecurity enhances data protection and safeguards business assets.
AI is a threat but with every risk there is opportunity. Security and GRC vendors constantly have fuel for their product development fire as generative AI increases the effectiveness of ingress methods such as successful phishing attempts. A recent study shows a 60% increase on multistage payload attacks which is a shift towards more complex attacks. As threats increase security vendors enhance their offerings with AI engine-based heuristics as countermeasures. Many vendors such as Microsoft Security Copilot, Darktrace, Obsidian and other vendors approach this with tools like security posture management. The approach is to “defend with X if attacked by Y” resulting in a 90%-time reduction in threat triage.
Advancements in Monitoring and Observability:
The introduction of generative AI has introduced
transformative possibilities for the field of Information Technology (IT). It
offers businesses novel avenues to enhance observability and monitoring, which
are critical components of IT operations.
Generative AI can significantly streamline the process of analyzing the copious amounts of logs and data our systems produce and compliance states we must retain. The only value in the data is the value driven from it. During a security breach every second counts and during an outage MTTR is contingent of quick root cause determination. Furthermore, by employing machine learning models, it can detect anomalies, trends, and potential issues in real-time. This capability is invaluable for IT teams, as it helps them proactively address problems before they escalate, thereby minimizing downtime and service disruptions.
Generative AI models can be trained on historical IT infrastructure data to predict equipment failures or performance degradation. This enables businesses to schedule maintenance activities at optimal times, reducing the risk of costly downtimes and enhancing overall system reliability.
Generative AI can even go a step further by using an AI Chat bot for frontline support in a more intuitive manner, accelerating issue resolution and improving the end-user experience.
From a reporting perspective generative AI can assist in creating dynamic dashboards and reports providing all business levels a comprehensive view of system health, capacity, and performance. Support facing dashboards can aid in informed decision making and rapid identification of areas that need resolutions. We can stop blaming the network team for CPU RDY issues. I can only imagine what I can do with my favorite tool vROPs (now Aria) with an added layer of prediction on top of my super metrics.
However, alongside these advantages, there are ethical considerations and challenges. The misuse of generative AI in manipulating monitoring data or generating misleading reports can undermine the integrity of IT systems. Therefore, it is imperative that organizations establish clear guidelines and oversight mechanisms to ensure that AI-driven observability and monitoring processes adhere to ethical and regulatory standards. Which brings us to our last but most important section.
Ethical Considerations:
Generative AI, like any emerging technology, brings forth a
host of ethical concerns. The potential for misuse, whether through the
creation of AI-generated content or the development of deepfake technology,
presents serious threats to privacy, security, and personal integrity. To
address these challenges, it is imperative to establish robust ethical
frameworks and regulations, thereby mitigating risks and ensuring the
responsible use of generative AI.
This discussion refrains from delving into illicit applications of AI technologies that venture into criminal realms. Instead, it underscores the necessity of assessing the ethical implications of adopting new technology and determining the appropriate parameters for its implementation.
Conclusion:
Generative AI has emerged as a game-changer in the digital
landscape, transforming industries and unlocking new possibilities. From
unleashing creativity to enhancing product designs and improving healthcare
outcomes, the potential of generative AI is vast. While ethical considerations
must be addressed, the benefits of generative AI far outweigh the challenges. As
we continue to embrace this technology, collaborative efforts among
researchers, policymakers, and industry leaders are essential to harness the
full potential of generative AI and drive a positive impact for society.
Make sure your data and compliance are in place, understand your data labels and owners, make ensure you are agile in deployment (hint – containers), and break silos of data or else you won’t break boundaries to true data value. Ultimately, it is crucial to emphasize that the true value of data is realized through the synergy of people and processes. Technology, while indispensable, is only a part of the equation. Without these key human and procedural elements, technological efforts may fall short of delivering their full potential.
If we don’t have the right humans and processes to create our superhero illustrations, we just end up with Will Ferrell and kittens in space.
- As a
disclaimer, this article was not written using AI but was refined for tone
and style to ease in the final review process for presentation.
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