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As part of Solutions Review’s Contributed Content Series<\/a>\u2014a collection of articles written by industry thought leaders in maturing software categories\u2014Rick Rider, the V<\/span>ice President<\/span> of Product Management at Infor<\/a>, explains why enterprise simulations can help your company onboard emerging technologies (like generative AI).<\/span><\/span><\/strong><\/em><\/p>\n Whether pursuing early adoption or taking a measured approach, the way companies react to new generative AI tools, such as ChatGPT and others, tells a lot about their approach to innovation.\u00a0<\/span>As we experience the AI renaissance and businesses turn their attention to modernizing processes, new enterprise software solutions powered by generative AI will become a large part of how companies embrace change. Generative AI is increasingly seen as a solution that can help enterprises make large-scale decisions to reduce inefficiencies and costs while driving growth.<\/span>\u00a0<\/span><\/p>\n However, the promise of emerging technologies must be taken with a degree of caution and consideration. Today, it is paramount for companies to critically analyze their approach to innovation and draw in team members and stakeholders from various roles and disciplines to help inform their path forward.\u00a0<\/span>\u00a0<\/span><\/p>\n Companies must allow for creative team approaches and new ideas without impacting their businesses. According to<\/a><\/span> Gartner<\/span><\/a>, <\/span>fusion team models are becoming increasingly important to enterprises to design, deliver, and improve digital offerings. For background, a fusion team is defined as a multidisciplinary team that blends technology or analytics and business domain expertise and shares accountability for business and technology outcomes. To effectively transform to a fusion team model and democratize digital delivery by design, <\/span>Gartner<\/span> points to the importance of composable technology, which enables businesses to create custom software applications composed of freely interchangeable components to support rapid and secure digital capability growth. <\/span>\u00a0<\/span><\/p>\n With these findings in mind, companies poised for success will partner with various teams within their organization and their customers to help create new ideas, products, and solutions. For example, companies that embrace creative team approaches and prioritize agility have likely welcomed the possibilities of ChatGPT and other new and emerging technologies shaping the future of how enterprises work. <\/span>\u00a0<\/span><\/p>\n An advantageous way that businesses are enabling creative and holistic approaches to innovation is by leveraging the practice of enterprise simulations. Today, companies often need to simulate decision-making with large amounts of contributing sources and data. In the case of generative AI, the technology will add to the available data pools for connected patterns and data. <\/span>\u00a0<\/span><\/p>\n Similarly, generative AI models can be formidable allies to the industry-specific machine learning and deep learning models used for simulations. Large Language Models (LLMs) can aid data scientists by generating the test data quickly and with a low barrier of natural language prompts. As the demand for enterprise simulations grows, combining these new technologies is an efficient mix that empowers businesses, encourages them to experiment with new practices at a significantly lower cost and time, and delivers solutions to meet the demands of transforming industries. <\/span>\u00a0<\/span><\/p>\n For example, businesses can leverage an enterprise simulation strategy to create a “digital twin” on business segments to properly test theories and ultimately make more informed decisions, such as changing production levels. Business simulations have been around for a while to coach and teach students. Still, this application focuses on building simulation environments specific to one’s organization and all the details and intricacies. By leveraging a business simulation, organizations can take a deeper look into the details and intricacies of their business. Furthermore, organizations can utilize these insights to improve processes.<\/span>\u00a0<\/span><\/p>\n When businesses move from storing large volumes of data loads to extracting key and meaningful insights from simulations, they are well on their way to better-informed decision-making and growth. Generative AI tools such as ChatGPT now introduce additional opportunities to interact and create enterprise simulations to inform decisions quickly and easily.<\/span>\u00a0<\/span><\/p>\n Generative AI and recent cases involving ChatGPT remind businesses to proceed with adopting newer technologies with a degree of caution. Inaccuracies, biases, and privacy concerns require keen human oversight. <\/span>\u00a0<\/span><\/p>\n To help organizations safely leverage generative AI models, it will behoove leaders and teams alike to leverage safety filers and attributes to promote the responsible use of AI. Users turn to filters to mitigate risks using new AI models to inform more reliable outputs. For example, Vertex AI, a machine learning platform that enables users to customize Large Language Models for use in AI-powered applications, processes and assesses content, filtering sensitive and potentially “harmful” outputs. <\/span>\u00a0<\/span><\/p>\n An additional approach is using training models using enterprises’ unbiased data. As the widespread adoption of AI tools unfolds, users will be introduced to more ways to overcome the challenges of accuracy, data privacy, and biases associated with using the technology. Enterprises that adopt the new technology earlier on improve the literacy and capabilities of generative AI to drive digital growth.<\/span>\u00a0<\/span><\/p>\n Over the past decade, the technology industry has witnessed many emerging technologies that have shifted the course of business as we know it\u2014from the notion of “Big Data” to the Internet of Things (IoT). It’s no secret that generative AI is the transformative technology of the year (and possibly many years). However, it is essential not to get swept up in the promise of how emerging technologies can uplevel businesses. Moreover, it is important to approach disruptive technologies strategically.<\/span><\/p>\n As the pace of innovation increases and businesses continue to evaluate their agility to embrace new technologies, enterprises that leave room for creative team approaches will adapt to the changing technology landscape ahead of competitors.<\/span><\/p>\n As part of Solutions Review’s Contributed Content Series\u2014a collection of articles written by industry thought leaders in maturing software categories\u2014Rick Rider, the Vice President of Product Management at Infor, explains why enterprise simulations can help your company onboard emerging technologies (like generative AI). Whether pursuing early adoption or taking a measured approach, the way companies […]<\/p>\n","protected":false},"author":633,"featured_media":6247,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[5],"tags":[2963,3037,3035,2857,671,3036,3038],"acf":[],"yoast_head":"\nTaking a Methodical, Strategic, and Creative Approach to Innovation <\/span><\/b>\u00a0<\/span><\/h3>\n
Trying Before Buying: The Enterprise Simulation Solution\u00a0<\/span><\/b>\u00a0<\/span><\/h3>\n
Proceed with Caution<\/span><\/b>\u00a0<\/span><\/h3>\n
A Step Forward<\/span><\/b>\u00a0<\/span><\/h3>\n
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