For some organizations, harnessing artificial intelligence’s (AI’s) full potential begins tentatively with explorations of select enterprise opportunities and a few potential use cases. While testing the waters this way may deliver valuable insights, it likely won’t be enough to make your company a market maker.
To become a true AI-fueled organization, a company may need to fundamentally rethink the way humans and machines interact within working environments. Executives must consider how to deploy machine learning and other cognitive tools systematically across every core business process and enterprise operation to support data-driven decision-making. In the end, the whole company must be open to AI driving new offerings and business models.
These are not minor steps, but as AI technologies standardize rapidly across industries, becoming an AI-fueled organization will likely be more than a strategy for success—it could be table stakes for survival.
No two companies will adopt a technology trend in the same way. Every organization has its own goals, strengths, and weaknesses to ponder before it embarks on its own transformation journey. If you are unclear about what the AI-fueled trend offers—or requires of—your organization, ask yourself the following questions:
What business objective(s) can our organization achieve by deploying artificial intelligence?
Artificial intelligence may offer a wealth of benefits to your organization, but only when viewed through a strategic business lens rather than as an IT project, and only when brand rhetoric gives way to measurable results. Collaborate across functions to identify the enterprise’s main objectives, then align the AI strategy to achieve those outcomes. You may choose to pursue solutions that reduce costs, facilitate a leap in productivity, monitor compliance, reduce risk scenarios, or derive greater meaning from more data. The first step of the AI journey should be setting end goals, which will enable you to draw a much more detailed, actionable road map with clearly marked milestones.
How can I use AI to achieve a competitive advantage?
AI is a broad category that includes natural language processing, computer vision, machine learning, and more, all of which can augment back-office, intra-office, and customer-facing systems. If you’re not sure where to start, look to your organization’s vertical industry for guidance and inspiration. Proceeding with an eye on your industry’s trends can ensure that you’ll both meet customers’ needs and remain competitive. For example, in the financial services industry, developers are creating highly personalized products and services; a financial firm may want to initiate its AI pilots by creating a robo-adviser or chatbot that can offer customers one-on-one investment advice. Deriving your initial AI pilots and use cases from your industry’s trajectory—which you can understand better by talking to customers, vendors, and industry analysts—helps ensure that your resources are utilized to meet business goals.
Is my technology adequate for an AI-fueled organization? If not, how do I find the right partners to build my AI ecosystem?
As you move forward, your organization’s existing technology and talent pool may be inadequate to meet the needs of standing up an AI system. You might look to bring in next-generation intellectual property, products, and solutions to broaden your ecosystem. Once you’ve determined where AI fits into your business processes, you can evaluate your existing technology, talent, and expertise to determine where there are gaps. You may decide to augment your existing resources by investing in startups that are further along in their AI journeys, or you may identify vendors and other industry partners with whom to collaborate and potentially co-invest in building market-ready applications with shared resources.
I’m sensing “cognitive fatigue” in my IT organization. What should I do?
There are companies that dove headfirst into cognitive approaches only to realize that they had taken on too much, too soon. Underwhelming results from early cognitive initiatives can dampen enthusiasm for further exploration. If you find yourself in this situation, consider starting a “lessons learned” dialogue with stakeholders and IT talent to review what went wrong and what can be done differently in future initiatives. And discuss AI approaches that other companies in your industry have taken that delivered desired outcomes.
Do I think big and start small—or go all-in?
More important than going big or starting small is moving purposefully. CIOs and business leaders appear to recognize the value of creating a long-term AI strategy to guide their efforts. Stay focused on the desired outcome, employ design thinking, and the right plan will fall into place. Begin by identifying opportunities for AI within your organization, such as transactional, time-consuming tasks or data-heavy processes that require a bit of “tribal” knowledge. Carry out a cost-benefit analysis to determine whether an AI solution is feasible for that process, taking into consideration both existing resources and those you will need to acquire. Next, structure a pilot program around one of those transactions to run four to eight weeks. If those results are positive, you’re ready to determine how you can move forward to scale to production and eventually expand to other products and service lines.
AI’s role in the enterprise is growing as cognitive tools and tactics are standardized across IT environments. While it is true that in coming years AI will likely be deployed not only to augment human performance but also to automate some operational and business processes altogether, proactively printing pink slips is an ineffective means of planning for the next cognitive stage. Now is the time to fundamentally rethink the way humans and machines interact within working environments and what they can achieve together in the AI-fueled organization of the future.
Read more about how companies are using AI to fuel growth and survival.
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