Remember the excitement when robotic process automation (RPA) became mainstream? Enthusiasts were excited to band-aid integrations over legacy systems and automate complex data entry forms to improve productivity and quality. Many organizations realized these benefits and saw an ROI from RPA, but only a few translated them into true digital transformational impacts.
Keep in mind that I have a high-bar definition of digital transformation from back in 2015, which I expanded on in my book, Driving Digital. My definition: “Digital Transformation is about looking at the business strategy through the lens of technical capabilities and how that changes how you are operating and generating revenues.”
Two key aspects of my definition: (i) transformation impacts the business strategy, and (ii) it requires both operational efficiencies and growing revenue. I expanded on this definition again in 2022 around hybrid working, evolving customer experiences, and data/analytics/ML capabilities.
Productivity improvements are not directly transformational
What’s lacking in my definition of digital transformation? You guessed it –
productivity.
Productivity doesn’t change business models. It’s an efficiency that can
improve profitability, quality, and scalability. However, transformation
stemming from productivity improvements only develops when people use the
freed-up time to generate innovation opportunities, including products,
service capabilities, and improved customer experiences.
Many of the quick wins from genAI are productivity drivers. Copilots in your
office suite and other workflow applications? -> productivity drivers.
Copilots generating code? -> Productivity drivers. Marketing SaaS tools
with AI content-generating capabilities? You guessed it, these are
productivity drivers, and their outcomes must be evaluated for
transformative impacts.
I’m not belittling these accomplishments and genAI value propositions. They
can be game-changing, especially when AI provides a skill the organization
has in limited supply or talent. It can be revolutionary when AI performs
complex tasks at scale, such as computer vision applications and AIs
integrated with robotics. And there is a financial ROI, with top cost-saving
opportunities in HR and IT, and the greatest revenue opportunities reported
in supply chain and marketing, according to a recent
McKinsey Global Survey on AI.
Look for productivity’s derivative opportunities
Digital Trailblazers
can find digital transformation from gen AI, but it requires looking beyond
productivity-improvement use cases. Try answering this question, “With
greater productivity and new creative capabilities from genAI, the business
model is evolving to X with Y transformative benefits.”
For example, low-code and no-code platforms like Appian, AWS, Pega,
Quickbase, and SAP have new genAI tools that enable non-coders and
non-technologists to use natural language for building applications. It’s a
productivity driver and opens app development to more departments and
end-users. However, digital transformation will be gauged based on the
developed applications and where they are game-changers to the business
model.
Another example is in customer service, where genAI improves case deflection
rates, and reps with gen AI provide better customer experiences. In the
2024 AI in CX benchmark report, deflection rates improved by 16-38%, and CSat (customer satisfaction)
improved by 84-92%, depending on the type of AI solution.
Developing CDPs (customer data profiles) and layering on other emerging technologies,
such as multilingual voice recognition and generation, can achieve more
transformative impacts in customer service.
“While productivity improvements are a huge benefit of Generative AI, that’s
simply scratching the surface,” says Yishay Carmiel, CEO of
Meaning. “Speech technology can
enable customer service agents and callers to bypass language barriers that
can lead to confusion and unresolved issues. By harmonizing conversation,
GenAI-powered speech tech has been proven to increase close rates
(inbound/outbound sales), decrease customer churn, and help to drive down
attrition.”
A third example is how GenAI can open up predictive analytics capabilities
to more departments and business leaders. Analytics can extend beyond the
world of data scientists, apps integrated with ML models, and dashboards to
one where more business professionals can use natural language to ask
analytical questions.
“AI can offer organizations the chance to dig into predictive analytics,
analyzing vast volumes of data to forecast and anticipate future trends and
outcomes with greater accuracy than ever before,” Says Jerod Johnson, senior
technology evangelist at CData. “In an
age of rapidly evolving markets, businesses can gain a competitive edge by
leveraging AI to proactively address challenges, optimize resources, and
plan for the future.”
GenAI’s digital transformation opportunities
We are seeing the opportunity for genAI to drive digital transformation in
some areas. Certainly, a new breed of startups is building products with AI
that are fundamental to their value propositions and user experiences.
But what about transformation in non-tech, non-SaaS businesses? Below are
some examples of the potential for digital transformation in several
industries:
- Healthcare: This sector may have the most transformative opportunities in areas like improving doctor workflow, accelerating gene-disease research, and equipping home care professionals with rapid information.
- Pharmaceuticals: GenAI coupled with ML is helping to accelerate drug discovery and lower the time and cost for FDA approvals.
- Manufacturing: GenAI is used in product design, predictive maintenance, and workforce training.
- Banking: Front-office applications include virtual bankers and investment research, but the bulk of the opportunity is in the mid-office in areas like KYC (know your customer), contract management, and commercial lending.
- Commercial real estate: GenAI can support property operations, acquisition strategy, and portfolio planning.
GenAI is sending sticker shocks
to CIOs as spending can easily outpace productivity benefits, financial
returns, and transformational results. It’s hard to show ROI in emerging
technology areas only from productivity improvements, cost savings, and
incremental revenue opportunities. Recall that digital transformation
requires realizing operational and growth opportunities.
CIOs need to find where genAI is going to drive digital transformation. I
published these recommendations last year on
adding genAI to digital transformation strategies:
- Define a game-changing LLM strategy
- Mitigate risks by communicating an AI governance model
- Re-evaluate decision-making processes and authorities
Contact me
for help with genAI blue sky planning and developing an AI governance
plan.
Digital Trailblazers! Join us Fridays at 11am ET for a live audio discussion on digital
transformation topics: innovation, product management, agile, DevOps,
data governance, and more!
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