![\"Retail](\"https:\/\/dmsretail.com\/RetailNews\/wp-content\/uploads\/2022\/05\/RETAIL-ONLINE-TRAINING-728-X-90.png\")
<\/a><\/p>\n<\/p>\n
I\u2019ll never cease to be amazed by the Olympic runners. As someone who has logged my fair share of runs, I\u2019m totally mesmerized by these runners\u2019 paces. I get short of breath just watching them on my TV.<\/p>\n
Olympic runners are worthy of our admiration. But these athletes didn\u2019t wake up the day before the Olympics and decide to hop a flight to Paris. Their freedom<\/em> to run at break-neck speed required years of discipline<\/em> and training.<\/p>\n They had a method. They trained. Step-by-step. Day-by-day. Until, one day in Paris, they were finally able to harness this power.<\/p>\n This is how we should view AI.<\/p>\n Just like training to be expert runner, a recent Gartner\u00ae report (which you can access here complimentarily) emphasizes the importance of a measured approach. According to Gartner, \u201cThe building blocks of AI adoption are various and diverse in real life. Nevertheless, when assembled, they follow general principles that support AI progress.\u201d Gartner mentions that \u201capplying these principles is necessary to set realistic expectations, avoid common pitfalls, and keep AI initiatives on track.\u201d<\/p>\n You can\u2019t be in the Olympics on day one \u2014 nor do you want to be in the Olympics on day one. Growing into an AI-mature organization is about following a roadmap \u2014\u202fa proven method \u2014 and not biting off more than you can chew.<\/p>\n By defining a clear strategy, communicating frequently, and setting measurable outcomes, organizations can optimize their results and avoid common pitfalls.<\/p>\n AI can help you classify and understand complex sets of data, automate decisions without human intervention, and generate anything from content to code by\u00a0utilizing large repositories of data. However, if you underestimate the importance of getting your priorities in order first, you may be forced to learn the hard way and suffer delays and frustration.<\/p>\n In the report, Gartner offers an AI adoption framework where \u201corganizations will avoid major pitfalls and maximize the chances of successful AI implementation.\u201d Gartner tells organizations to \u201cuse the AI adoption curve to identify and achieve your goals for activities that increase AI value creation by solving business problems better, faster, at a lower cost and with greater convenience.\u201d<\/p>\n Let\u2019s look at our takeaways from these key phases.<\/p>\n Start small. Getting into peak running condition starts with short runs. Identify and recruit an internal champion to help socialize efforts and secure support from key stakeholders. Establish three to six use cases with measurable outcomes that benefit your line of business.<\/p>\n Practice makes perfect. Invest in the humans, processes, and technology that ease the transition between phases, such as funding a Center of Excellence (COE) and teaching practical knowledge of cloud AI APIs. Build executive awareness with realistic goals. Experiment. Break things. And don\u2019t be afraid to change course on your strategy. Be flexible and know when to pivot!<\/p>\n At this point in the process, you have a basic AI governance model in place. The first AI use cases are in production, and your initial AI implementation team has working policies to mitigate risks and assure compliance. This stage is referred to as the \u201cpivotal point\u201d \u2014 it is all about stabilizing your plans, so you are ready to expand with additional, more complex use cases.<\/p>\n With strategic objectives defined, budgets in place, AI experts on hand, and technology at the ready, you can finalize an organizational structure and complete the processes for the development and deployment of AI.<\/p>\n High costs are common at this stage of AI adoption as initial use cases prove their value and momentum builds. It\u2019s natural to hire more staff, upskill employees, and incur infrastructure costs as the wider organization takes advantage of AI in daily operations.<\/p>\n Track spending and be sure to demonstrate progress against goals to learn from your efforts. Socialize outcomes with stakeholders for transparency. Remember, just like run training, it\u2019s a process of steady improvement. Track your results, show progress, and build on your momentum. As you grow more experienced, you should expand, evolve, and optimize. Providing your organization sees measurable results, consider advancing efforts to support more high risk\/high reward use cases.<\/p>\n AI will succeed in an organization that fosters transparency, training, and shared usage of across business units, not limited to exclusive access. Build an \u201cAI first\u201d culture from the top down, where all workers understand the strengths and weaknesses of AI to be productive and innovate security.<\/p>\n AI adoption will vary and that\u2019s okay! Follow these steps to ensure you stay on the path most appropriate for your business. Avoid common mistakes of caving to peer pressure and focus on creating a responsible use of AI that enables you to reduce technology risks and work within the resources currently available. Here\u2019s some advice from those that hit a speedbump or two.<\/p>\n According to Gartner, \u201cBy 2025, 70% of enterprises will have operationalized AI architectures due to the rapid maturity of AI orchestration platforms.\u201d Don\u2019t get discouraged if you are in the 30% that may not be on that path.<\/p>\n Every organization will choose to adopt AI at the rate that is right for them. Some organizations consider themselves laggards, but they are learning from their peers and are taking the necessary steps to create a successful AI implementation. \u201cBy 2028, 50% of organizations will have replaced time-consuming bottom-up forecasting approaches with AI, resulting in autonomous operational, demand, and other types of planning.\u201d<\/p>\n Read the complementary report to learn more about key adoption indicators and recommendations to ensure data is central to your strategy\u2014from determining availability, to integration, access and more. This Gartner report provides hands-on, practical tips to help build confidence with tips and recommendations to help embrace the AI journey from planning to expansion.<\/p>\n \u00a0<\/p>\n \u00a0<\/p>\n \u00a0<\/p>\n Share:<\/p>\n \n \t<\/div>\n![\"\"](\"https:\/\/storage.googleapis.com\/blogs-images\/ciscoblogs\/1\/2024\/08\/AdobeStock_537380837-scaled.jpg\")
<\/p>\nThe Gartner phased approach to AI adoption<\/strong><\/h2>\n
Phase 1. Planning<\/strong><\/h3>\n
Phase 2. Experimentation<\/strong><\/h3>\n
Phase 3. Stabilization<\/strong><\/h3>\n
Phase 4. Expansion<\/strong><\/h3>\n
Phase 5. Leadership<\/strong><\/h3>\n
Lessons from the AI graveyard<\/strong><\/h2>\n
\n
No two AI journeys are the same<\/strong><\/h2>\n
Read the report:<\/strong><\/h3>\n
Gartner, Become an AI-First Organization: 5 Critical AI Adoption Phases, Svetlana Sicular, Bern Elliot, Jim Hare, Whit Andrews, 13 October 2023
GARTNER is a registered trademark and service mark of Gartner, Inc. and\/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.<\/h5>\n