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Artificial intelligence (AI) isn\u2019t the only thing at the heart of what organizations are doing to keep with digital transformation and drive business growth. People are, too. <\/p>\n\n\n\n
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\u2019s accessible to just about everyone. Wheels are turning faster than we\u2019ve seen – we\u2019re reaching a level of computing power, large data sets, extensive language models, and more that can bring forth excitement for people, yet startle others. <\/p>\n\n\n\n
A frenzy of conversations and headlines, including genAI\u2019s 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<\/a> reported. <\/p>\n\n\n\n But reaching goals collectively isn\u2019t about replacing humans. It\u2019s about augmenting people in an AI-friendly culture.\u00a0<\/p>\n\n\n\n <\/p>\n\n\n\n The opportunity is here. <\/p>\n\n\n\n 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\u2019s a necessity for continually scaling economies without the labor rate we\u2019ve seen in previous decades. <\/p>\n\n\n\n At the business level, it\u2019s 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 \u2013 and this includes leaders. <\/p>\n\n\n\n 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\u2019t, like creativity and imagination. <\/p>\n\n\n\n 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.\u00a0<\/p>\n\n\n\n <\/p>\n\n\n\n <\/p>\n\n\n\n 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. <\/p>\n\n\n\n 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\u2019re 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. <\/p>\n\n\n\n As AI is increasingly applied to business problems, so is the AI culture\u2019s 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\u2019s talent and training strategies to manage potential confusion, misunderstanding, and excitement about AI. It\u2019s about bringing people along to capitalize on operationalizing AI.\u00a0\u00a0<\/p>\n\n\n\n <\/p>\n\n\n\n <\/p>\n\n\n\n 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. <\/p>\n\n\n\n We’re using AI to create new tools that can be scaled further than before. It\u2019s important to make it digestible, and always map AI to the data, establish desired outcomes, and decide how to achieve them. <\/p>\n\n\n\n It\u2019s also important to consider how AI will be used. AI can automate single tasks and help solve problems, but it\u2019s 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 \u201cpower moves\u201d will answer that question, as well as help IT and business leaders strategize AI to drive business results.\u00a0\u00a0<\/p>\n\n\n\n <\/p>\n\n\n\n <\/p>\n\n\n\n Today\u2019s shortage of IT talent doesn\u2019t equate to the level of digitalization we have and priorities we\u2019ve 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\u2019t be automated. With no automation in IT, there\u2019s no escape from falling behind, especially as today\u2019s pace of innovation continues to ramp up. <\/p>\n\n\n\n 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\u2019re getting. IT wants the outcomes of always-on infrastructure, and the ability to utilize automation as much as possible. <\/p>\n\n\n\n In terms of mapping AI initiatives to business outcomes, CIOs and business leaders should determine what\u2019s keeping the business from growing and adding unnecessary costs. What\u2019s 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. <\/p>\n\n\n\n From there, it\u2019s 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.\u00a0\u00a0<\/p>\n\n\n\n <\/p>\n\n\n\n <\/p>\n\n\n\n For enterprise maturity, there\u2019s an understanding that leaders are managing the company with the staff they have today, but thinking about who they\u2019ll 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.\u00a0<\/p>\n\n\n\n In AIOps today, teams have to understand many types of alerts, complete the event correlation, detect what\u2019s real and what\u2019s 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\u2019t get there in a day, but rather by a slow-and-steady combination of people process and technology (chatbots, voice assistants, etc.). <\/p>\n\n\n\n More AI applications have become particularly useful (in AI, automation, ChatGPT, etc.), but they\u2019re 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\u2019t completely resolve, and so human staff will need to problem solve through the insufficient data. <\/p>\n\n\n\n Driving business value comes from full orchestration, but can start with addressing the most obvious problems \u2013 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. <\/p>\n\n\n\n Why haven\u2019t 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 \u2026 and possible. <\/p>\n\n\n\n Many organizations just aren\u2019t 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\u2019s 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 \u2013 the foundation for driving growth.\u00a0\u00a0<\/p>\n\n\n\n <\/p>\n\n\n\n <\/p>\n\n\n\n Without a people strategy, organizations can\u2019t 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. <\/p>\n\n\n\n Plus, creativity prevents AI from working alone, as AI simply isn\u2019t good at it. People supply the real ideas and desires to enhance the products and services we buy \u2013 this is where the power to add value lies. Entertainment, like movies and sporting events for example, require the minds of people \u2013 creativity in the human element. As consumers, we want outlets that cannot be provided by AI, even with creativity-like programming. <\/p>\n\n\n\n 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. <\/p>\n\n\n\n Nonetheless, more AI and automation is needed today than in the past for enhancing business productivity, supporting organizational growth, and strengthening today\u2019s gross domestic product (GDP). When people and AI join forces, creativity and innovation meet efficiency and productivity, which drives greater results and sustained success. <\/p>\n\n\n\n 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<\/a>!<\/p>\n\n\n\nCorrectly Applying AI for Optimal Business Impact\u00a0\u00a0<\/h3>\n\n\n\n
How an AI Culture Can Mitigate AI Concerns<\/strong> <\/h3>\n\n\n\n
First Things first: Start Thinking About AI and Achievements<\/strong> <\/h3>\n\n\n\n
1. Map AI Initiatives to Business Outcomes: Clearly Align Business Goals and How You\u2019ll Operationalize AI<\/strong> <\/h3>\n\n\n\n
2. Think Big, But Start Realistically: What\u2019s Needed to Achieve Outcomes?\u00a0<\/h3>\n\n\n\n
3: AI + People = Better Together: AI Without People is Just Artificial Without the Intelligence<\/strong> <\/h3>\n\n\n\n