Artificial intelligence (AI) isn’t the only thing at the heart of what organizations are doing to keep with digital transformation and drive business growth. People are, too.
Development of AI actually began about 40 years ago, but for generative AI (genAI), that time is much less. The explosion of genAI has brought about an everlasting, first-of-its-kind innovation that’s accessible to just about everyone. Wheels are turning faster than we’ve seen – we’re reaching a level of computing power, large data sets, extensive language models, and more that can bring forth excitement for people, yet startle others.
A frenzy of conversations and headlines, including genAI’s promise to open new dimensions of AI and start replacing people continue to thrill some, but unfortunately, worry others. In Hollywood on July 14, for example, actors began demonstrating in picket lines rather than performing on set in protest of AI-generated actors replacing their IRL (in real life) talent. From stars to extras, actors want protection against AI, The Guardian reported.
But reaching goals collectively isn’t about replacing humans. It’s about augmenting people in an AI-friendly culture.
Correctly Applying AI for Optimal Business Impact
The opportunity is here.
AI is being adopted at a quick pace and gaining significant business presence. Organizations of all industries are realizing the value of AI in bringing positive change to the business, and the role it plays in economic growth. U.S. labor growth has reached the inability to support economic growth without AI. It’s a necessity for continually scaling economies without the labor rate we’ve seen in previous decades.
At the business level, it’s about employing AI where it makes sense. Working alongside human teams, AI drives productivity during economic ups and downs, and as new technology options are introduced, it creates the need to retrain employees – and this includes leaders.
Leaders are responsible for training an AI-friendly culture to drive business results. The workforce has to learn how to be more valuable in a world where AI is increasingly available, which includes upskilling and reskilling, and producing things that machines can’t, like creativity and imagination.
When applied correctly, AI can create higher performing, more profitable companies. Leaders who speak to AI in shareholder briefings, for example, can also speak to an increase in their stock pricing, which helps provide understanding that when applied properly, AI can drive greater shareholder returns.
How an AI Culture Can Mitigate AI Concerns
When it comes to operationalizing AI, organizations have high concerns about government and security risks, technological complexity, and lack of clarity on ROI and challenges with accuracy. Companies feel a sense of urgency to implement AI, but its value is not yet clear.
Different types of AI have different business values depending on how they apply them. For example, if a company has very secure data that they’re running machine learning or other training models on, then security is part of their regular processes. But when starting to run genAI models that look outside the company’s secure, validated data, companies will question privacy, data, security, and even the cleanliness of data.
As AI is increasingly applied to business problems, so is the AI culture’s tie to the business. Organizations must educate their entire population (employees, consumers, etc.) on what AI means to them and the safe ways it should be used. AI will grow its presence in day-to-day life, and with that expansion comes the need to change the organization’s talent and training strategies to manage potential confusion, misunderstanding, and excitement about AI. It’s about bringing people along to capitalize on operationalizing AI.
First Things first: Start Thinking About AI and Achievements
A primary business focus of doing things better and more efficiently, and delivering customer satisfaction, comes with determining what business outcomes the organization wants from AI, and then figuring out the right building blocks. Leaders can start by examining data on-hand and making sure employees understand that data.
We’re using AI to create new tools that can be scaled further than before. It’s important to make it digestible, and always map AI to the data, establish desired outcomes, and decide how to achieve them.
It’s also important to consider how AI will be used. AI can automate single tasks and help solve problems, but it’s better when crafted together as to scale automation to achieve greater business outcomes. So how should leaders think about implementing AI in their organization successfully? The following “power moves” will answer that question, as well as help IT and business leaders strategize AI to drive business results.
1. Map AI Initiatives to Business Outcomes: Clearly Align Business Goals and How You’ll Operationalize AI
Today’s shortage of IT talent doesn’t equate to the level of digitalization we have and priorities we’ve set. It illustrates a very real need for IT automation for which organizations should consider and then take action. It means removing manual, repetitive tasks and enabling more predictable IT work, and using human IT staff for complex, creative processes that can’t be automated. With no automation in IT, there’s no escape from falling behind, especially as today’s pace of innovation continues to ramp up.
Harnessing the power of AI in IT applies to everyone using software and technology, with key use cases including infrastructure availability, incident remediation, application availability, and more. CIOs and IT professionals must be aware of their own use cases, and get clear on the level of adoption and value they’re getting. IT wants the outcomes of always-on infrastructure, and the ability to utilize automation as much as possible.
In terms of mapping AI initiatives to business outcomes, CIOs and business leaders should determine what’s keeping the business from growing and adding unnecessary costs. What’s holding you back? Where would you like to see cost efficiency? Answering questions like these will help you apply AI and automation to business challenges, and then assess scalability and explore the maximum level of applicability.
From there, it’s about using automation to fuel growth, increase efficiency, and boost time to value. In IT, for example, goals could include achieving higher quality faster, generating faster releases, and maintaining greater self-healing. AI can be applied to existing processes in new, superior ways, or to problems that only had manual solutions. Teams then can leverage emerging capabilities to drive growth and take care of current, growth-related problems.
2. Think Big, But Start Realistically: What’s Needed to Achieve Outcomes?
For enterprise maturity, there’s an understanding that leaders are managing the company with the staff they have today, but thinking about who they’ll need tomorrow. For example, younger generations are quickly growing digital literacy skills. Leaders will need to advance that knowledge into a culture of AI literacy with coaching and training, and build it into the skills of the company.
In AIOps today, teams have to understand many types of alerts, complete the event correlation, detect what’s real and what’s not, and then take action. Automating the entire process might be a hefty goal, and with new technology comes potential impatience. Harnessing the hype of AI and automation means knowing you can’t get there in a day, but rather by a slow-and-steady combination of people process and technology (chatbots, voice assistants, etc.).
More AI applications have become particularly useful (in AI, automation, ChatGPT, etc.), but they’re not a solution for everything. After all, NASA still has its control center! If leaders can find their theoretical maximum, they can then pick out the most repetitive tasks, and track data to a specific outcome they want from AI. There might be occasional conflicting, inconclusive data points that AI can’t completely resolve, and so human staff will need to problem solve through the insufficient data.
Driving business value comes from full orchestration, but can start with addressing the most obvious problems – it’s the simplest way to get data, secure it, and build out a high-confidence result. Customers today want the greatest experiences possible, and scaling to deliver on those expectations with people is challenging. Augmenting workforces with AI can make meeting demands much easier.
Why haven’t we commercialized faster for business outcomes? Organizations need the technology and AI component, but also a business mindset with enough visibility of desired outcomes. It requires business acumen, a view of how the business could be better, and the operational information to know that your outcomes are meaningful … and possible.
Many organizations just aren’t sure what to automate or where to apply AI from the get-go. Getting started appropriately, with simple, repetitive tasks, will lead to process automation so long as there’s momentum. IT already has a lot of data coming from tickets, alerts, and monitoring. Learning about the state of the business will help reveal the best automation starting point – the foundation for driving growth.
3: AI + People = Better Together: AI Without People is Just Artificial Without the Intelligence
Without a people strategy, organizations can’t have an AI strategy. It takes human input and understanding to make AI better, which allows people to maintain control but optimize automation for various use cases.
Plus, creativity prevents AI from working alone, as AI simply isn’t good at it. People supply the real ideas and desires to enhance the products and services we buy – this is where the power to add value lies. Entertainment, like movies and sporting events for example, require the minds of people – creativity in the human element. As consumers, we want outlets that cannot be provided by AI, even with creativity-like programming.
In the workforce, especially as it relates to the economic and business trends, leaders must prioritize people, and help them learn, grow, and take advantage of development opportunities.
Nonetheless, more AI and automation is needed today than in the past for enhancing business productivity, supporting organizational growth, and strengthening today’s gross domestic product (GDP). When people and AI join forces, creativity and innovation meet efficiency and productivity, which drives greater results and sustained success.
Resolve is ready for your elite squad, to help you apply AI and automation for the best possible time to value and business outcomes. Get in touch!
Resolve and IFS recently held a fireside chat, “AI and The Future of IT Automation: 3 Power Moves to Harness the Hype” to share and discuss the full story, now available on-demand.