Overcoming AI Challenges with IBM’s AI Ladder

With IBM’s AI Ladder
Overcoming AI Challenges

© 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
With $16 trillion up for grabs by 2030, there’s a race to be leaders and pioneers
in the brave new world of AI and automation. Across every industry, we see an
acceleration in the rollout of smart, cognitive systems that promise improved
customer experience and streamlined more efficient business processes.
Inevitably this leads to the dreaded FOMO – fear of missing out – which in turn
leads to badly executed ideas, wastage, and missed opportunities. For me,
warning signs flash when I get the impression that leadership teams, often
chasing hype and buzzwords, are approaching the task of digital
transformation from a tech-first perspective rather than a problem-first or
customer-first perspective.

I believe that almost any business can benefit from the application of artificial
intelligence (AI). However, any business that sets off on such a mission is setting
itself up for failure if it doesn’t start by focusing on putting together a strategy for
AI and, specifically, data, which is the fuel of all AI engines.
Fortunately, a great deal of the groundwork has been done on this already –
strategic, mission-oriented thinking from many of the leaders in the field of business
technology is readily available. One such leader is IBM – a name that has been
synonymous with cutting-edge computing for over 100 years. For the last decade or
so, however, it has built a reputation as a leading supplier of AI-as-a-service
solutions, as well as the cloud and hybrid cloud infrastructures that make it possible
for any organization, regardless of its size, to join the AI revolution.

The AI Ladder
Setting out to integrate AI into business operations can seem like a daunting task.
do you start? We know AI can level up every aspect of a business’s performance, from
marketing to research and development, manufacturing, customer services, and any
number of back-office functions such as finance, logistics, and HR. Understanding
an organization will get the best bang-for-buck is essential. Then there are issues of
governance, compliance, regulation, and trust – it's vital to have a complete
understanding of the implications as they relate to your business, data, and customers,
but again, none of this comes without cost.
To help businesses navigate this tricky set of obstacles, IBM has created what it calls the
AI Ladder. As the name suggests, it’s a step-by-step framework that orders and explains
the most pressing challenges that must be tackled at every stage of the process a
company goes through during its evolution to the state of a smart enterprise.

Andrew Brown, General Manager for Technology at IBM UK & Ireland, sums it up
neatly: “A hybrid cloud and AI strategy allow businesses to leverage their existing
investments while adding new technologies rapidly and seamlessly for digital
advantage. We assist organizations with a prescriptive approach by architecting AI
into their data fabric, applications, and processes, enabling them to turn data into
insight, making applications more client centric and processes more agile.”
One statistic that IBM highlights is that 81% of business leaders admit that they
don’t understand the data and infrastructure requirements for adopting AI in their
organizations. The ladder is an attempt to formalize the learning process that needs
to be followed in order to fix this.
It has four steps – collect, organize, analyze and infuse.

To take a bit of a closer look into what is meant by each of them, collect refers to the
process of “making data simple and accessible.” This means breaking down siloes that
may have traditionally been a barrier to effective, organization-wide exploitation of data
resources, fully understanding the range of data that’s available (and how to find or
create the data that isn’t), and how to leverage tools that bring AI and smart automation
to the job of collecting, organizing and storing data itself.
“Organise” means to "create a business-ready analytics foundation." Once you’ve worked
out what data you need and how you’re going to collect it, you’re ready to tackle issues
such as data quality, how to catalog and store data so it will be ready for use when it's
needed, and identifying issues around access and governance of your data. The most
valuable data is often human data – and this is usually personal data, meaning it comes
with a high burden of regulation and compliance. Initiating automated processes to
ensure all of your data is stored and accessed appropriately is an essential step of the
ladder that companies can’t afford to skip.

“Analyse” requires businesses starting to work with AI to learn to "build and scale AI with
trust and transparency." This is where we develop and deploy the models and algorithms
that we use to wring insights from the data we've collected and organized in steps one
and two. If we've done it the right way, hopefully, it leads to insights that we can use to
improve our products and services, create internal efficiencies, or even create entirely new
business models based on smart, data-driven analytics.
The final step on the ladder is "infuse," which IBM defines as learning to "operationalize
AI throughout the business." Here we come to the tricky subject of building company-
wide cultures of data and tech-literacy. This means building an understanding of how
data flows through an organization – not just within one particular AI or analytics use
case, but how the process of generating insights in one area can be scaled out across an
entire business so best practices are adopted, from shop floor to boardroom, and lessons
learned can be applied anywhere, regardless of where the initial work was done.

Andrew Brown shares further insight into IBM’s approach: “We're focused on our client’s
core capabilities to create digital advantage - delivered on an open 'build once, deploy
anywhere' platform. And AI is an absolutely essential part of those capabilities. Whether
you apply AI to automate processes to reclaim time for higher-value work, make data-
driven predictions, secure business with real-time threat insights, or modernize your
environment for agility. The ability to architect for digital advantage, integrating across an
open technology ecosystem, is crucial to success.“
To illustrate this concept, IBM uses the example of a customer in the energy production
business that digitized the knowledge of the expert teams of engineers responsible for
the company’s success. This information can then be disseminated to employees
anywhere in the organization, where their insights can be re-used to drive efficiency and
innovation. In this case, AI is used to interpret the experts’ knowledge and experience in a
way that makes it valuable far beyond the domain where it was originally conceived.

Putting the ladder to work
The ladder is a great framework for approaching the initial challenges of adopting AI
a business. A very pertinent point the authors make is that "AI is not magic." Although
there have been a lot of heady promises about what can be achieved with AI, and
sometimes it's sold as a one-size-fits-all solution for companies that want to modernize
and leverage technology, it still requires a great deal of thought and planning before
positive results can be expected. Working with companies all over the world on their
AI transformations, I have seen first-hand how important a solid strategy and
is to success. Once that’s in place, the real fun of applying human imagination and
ingenuity to the task of creating AI-driven growth and success.

Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website
© 2020 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website

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Overcoming AI Challenges with IBM’s AI Ladder

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