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.