No gold rush comes without its pitfalls. Take a look at the scant records from California’s Gold Rush of the 1800s, and, along with the perceived opportunity that brought prospectors to the coast, you’ll find stories of hardship and tough times. That’s a colorful way of saying that, as we rush into the golden era of AI – as the cost of hardware plummets and algorithms evolve – it’s important to understand what we’re getting into.
As AI leaps from automated customer service bots to generative models that will touch every industry, let’s not be blinded by the unparalleled speed to market, or the scale of opportunity. Let’s focus on business strategies, guardrails, governance and structures that guarantee usage practices, ethics and actual benefits to businesses that are now scrambling to invest in, or embrace, anything AI.
I recently had the privilege of speaking at a generative AI (GenAI) event hosted by the EY organization and Microsoft alliance on these topics and more. If you missed that or you’re a leader who is exploring the next business step forward with AI, let’s take a closer look at what we all need to know.
AI mimics human intelligence in its responses, outputs and algorithmic ability to learn and adapt. And it has come in waves: First automated phone answering, then chatbots and machine learning. But this new tsunami of generative AI grabbing the headlines is a fast-burning fuse of everything that is to come in business and society.
It’s pushing the S-curve faster than anything we’ve seen, including the birth of the internet. A million users in the first five days and 100 million users from its late 2022 launch to January 2023. Since then, we’ve seen acceleration of industry announcements and strategic partnerships, including our own strategic alliance with Microsoft, centered around its Microsoft Azure suite of products and Open AI.
We’re now about to swing sharply from initial education of organizations and stakeholders toward proof-of-concept demands and tangible action around ideal architecture, processes, and the strategies to integrate AI and scale. This is the time and place where all executive leaders must lean in and collaborate.
The perennial question, only now with urgency. Why should organizations embrace AI, or even invest? Consider these four pillars that are now critical to understanding AI benefits beyond efficiency:
1 – Because GenAI tools require no-code knowledge for use, the democratization of access will dramatically broaden worker access to data insights.
2 – Generative AI will enable broader business creativity, problem-solving and decision-making, simplifying processes and reducing human error.
3 – In reality, most organizations run diagnostics vs. making real-time, data-driven decisions. AI will enable the use of near-real time data points in a wide variety of strategic decision-making processes.
4 – Powered by AI, data science will evolve from information processing to model building, to fine-tuning of data with a focus on storytelling.
How to begin AI integration
Whether you approach AI with the support of an experienced transformation collaborator like the EY organization that has an AI track record and process solutions, or not, engaging with it requires a thoughtful approach. Instead of assessing individual tools, you should first understand how GenAI can fit with your business infrastructure, goals and governance program. Look at mapping strategy; building a business case; evaluating risk; and defining guardrails, policies, procedures and model validation, and then create responsible AI practices as AI becomes a business and innovation tool.
Ways to monetize AI with your business
GenAI can play a significant role in helping organizations capture consumer trends and preferences through trend forecasting, pattern identification and market analysis. Writing tools can generate product descriptions that automatically incorporate the most relevant search terms and consumer feedback to drive better SEO and engagement. This accelerates better content deployment, meaning more frequent refreshes and updates to further engage consumers or users. Voice recognition can now extract key words from customer calls and write responses for improved reception and engagement.
In product development, GenAI can enhance innovation. For instance, tools can take unstructured data tied to consumer behavior and mapping themes, as well as perceptions and occasions, and use those inputs to inform text-to-image prompts that generate new digital renderings of prototypes. In our work with Microsoft Azure AI and DALL-E, for example, we use these AI tools to an analyze our clients’ first-party data of their prior inventory, which allows for rapid prototyping based on consumer insights.
Steps to model and culture shift
GenAI will democratize information access for your organization, which will require upskilling of employees. All will need a baseline understanding of AI tools and capabilities, but your business will require algorithmic understanding in-house and the ability to use AI learnings to make business decisions and act accordingly. Consider the dos and don’ts of using AI on the job.
Will AI-written reports be acceptable? How will the use of AI in more research and data gathering functions change people’s job roles and responsibilities? As AI generates more content, designs and ideas, the role of your workers will shift from primary creators to those of editors, curators or supervisors of AI-generated content. That means that, in the very near future, successful AI business integration will come down to a combination of the creative instincts, emotional intelligence and nuanced understanding of workers plus the generative outputs of AI. That’s a big shift for which businesses should start planning now, along with appropriate training, policies and procedures.
The other major shift to address is just what that access to instantly available knowledge can do for your business – and how it will reshape the speed at which you do business. AI will allow near-real-time understanding of customer sentiment and necessitate faster response times. Your business infrastructure will need to be based around agility and adaptability because 36- to 48-month change cycles will be neither acceptable nor practical to compete successfully. As you navigate this shift, don’t let the velocity of AI media coverage or board pressure detract you from the very real need to properly understand, plan for and integrate this shiny new functionality into real business structures and plans.
Shopping for AI
When it comes to selecting AI tools and integration, keep this in mind: AI is not an end-to-end scope like other off-the-shelf solutions. Organizational practice usually means developing a strategy, making long-term plans and then building a technology infrastructure to deliver it. Here, it’s more about trying an AI solution or idea and developing a proof of concept that can be built into longer-term plans. Everyone is in either a wait-and-see or figure-it-out mode as AI developments unravel quickly.
The last word
We’re on the precipice of society-wide change. And that’s not an exaggeration. Businesses must move and adapt quickly because the degree of progress from a single day in the evolution of AI could take weeks using other tools and technologies. As you gear up for increased speed to market, do two things: First, keep your hands on the wheel. Yes, move quickly, but put the plans, structures, training and tools in place that will help you achieve success. AI is no longer simply disrupting business – we are in the age of convergence, and you must be ready. Take a minute to visit ey.ai where you’ll find the tools to explore more about how to engage with GenAI for your business and your future.
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This Publication contains information in summary form and is therefore intended for general guidance only. It is not intended to be a substitute for detailed research or the exercise of professional judgment. Member firms of the global EY organization cannot accept responsibility for loss to any person relying on this article.