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IT’s New Machine Learning Strategy

At its core, technology exists to make certain tasks faster, cheaper, and easier to perform, all while delivering better results. Machine Learning (ML) is no different; the task it optimizes is identifying improvements and solving problems. From Netflix to Salesforce to Twitter, many of the world’s largest and most valuable companies are investing heavily in ML, betting on its value with their bottom lines. In fact, analysts expect corporations to commit $12.3 billion to machine learning by 2026, up nearly 5x from the $2.5 billion spent in 2017. But what about everyone else – all those companies that don’t have billions of dollars to commit to hiring ML engineers, developing proprietary AI, and building their own ML programs? How can we democratize ML so that even the smallest and most ambitious companies can get into the game and start using ML to improve how they do business? That’s where Machine Learning as a Service (MLaaS) comes in. Offering ready-made tools that can be easily adopted and fitted to various business needs, MLaaS removes many of the barriers that previously prevented smaller companies and their teams from tapping into the power of ML, including time, budget, and – most importantly – the ability to code. No-Code MLaaS democratizes the power of machine learning  No-code platforms like AppSheet are the backbone of MLaaS, and for good reason. With a no-code platform, anyone — regardless of their technological prowess or experience — can build robust applications that are driven by ML algorithms to solve problems, increase productivity, and deliver a healthier bottom line. These no-code development platforms extend the power of software development beyond the IT department to empower non-technical employees like business leads, employees who run on-the-ground processes, and subject matter experts to create customized business applications without writing code.  Equipped with no-code development platforms, “citizen developers” play pivotal roles in building apps that help move their teams and companies forward. Empowering non-technical workers to build their own solutions also frees up IT to focus on key strategic objectives, and helps eliminate the knowledge gap so that the workers closest to the problems are equipped to solve them directly, no matter their level of technical experience. 4 steps to unlocking your MLaaS strategy With the democratizing power of MLaaS and a no-code platform like AppSheet, you can embark on a new IT strategy that future-proofs your organization’s tech stack from the ground up and delivers continuous optimizations to every facet of your operations. Here are four key tips for unlocking IT’s new MLaaS strategy: Plan No-code MLaaS can optimize mission-critical processes across your entire organization. That’s a powerful prospect. The technology gives business leaders the insights and ability they need to revamp old tech stacks and future-proof companies from the ground up without re-starting at square one. No-code platforms make it easy for all employees to create custom applications that enable app creators and app users to tap directly into data sources. For example, data resting in a spreadsheet or database can be surfaced for strategic trends and predictive insights that can help shape that department’s strategy.  This direct connection between the data and the non-technical workforce enables citizen developers to transform the way work gets done, fully automating tasks and eliminating process gaps. But no-code doesn’t leave IT in the dark. Quite the contrary. The IT department establishes and maintains the governance guardrails for app building organization-wide. Without any coding experience, employees can create apps that not only extend the life and value of your legacy systems, but also bridge the gap between them, making it easier to connect  older systems with newer technologies so your organization can plan for the future and be prepared for whatever’s next. Invest A decision to use a no-code platform is an investment in your organization and IT department. MLaaS eliminates the pressure of developing ML systems and constantly creating and testing new business apps through the IT team’s workflow, relieving the strain on over-stretched developers. This frees up time for IT to focus on what they do best: Keeping critical processes and strategic initiatives humming at maximum efficiency. With MLaaS, the role of planning and execution moves from the IT and development teams to the people across your organization who know your company’s challenges best – from sales and marketing to HR and operations – all while supporting technical innovation and organizational growth. Evangelize The next step in any MLaaS strategy is to identify early adopters in your organization and get them on board. Who will see the most benefits from creating no-code apps? And how can you sell them on this solution? The key here is to help them understand the game-changing value of solving problems at an unprecedented scale by thinking creatively and building their own solutions. No-code MLaaS puts the control back in the hands of your employees, harnessing untapped problem-solving potential. Everyone across your company can perform better when they feel that leadership empowers them to make decisions and equips them with the tools they need to succeed. That’s exactly what we mean when we talk about the democratizing power of MLaaS. Iterate ML apps get smarter the more they’re used; that’s why it’s called Machine Learning. And the people who create these apps do, too. Perhaps the most important step in any MLaaS strategy is iteration. ML doesn’t just help your business run better; it continuously surfaces insights about your operations that you may never have even considered. As a result, app creators learn what’s possible and iterate more quickly using MLaaS. That means that your digital transformation isn’t a one-time event; it is a constant, ongoing process of improvement and optimization every single day so that your apps (and the people who create them) will perform even better tomorrow than they did yesterday.

The Citizen Developer’s Guide to Machine Learning as a Service

You’ve probably heard of machine learning, and you’ve almost certainly experienced it. Machine learning algorithms help power everything from Netflix’s personal movie recommendation engine to Google Search and Translate, and research suggests that companies will invest $12.3 billion in machine learning by 2026, up from the $2.5 billion spent in 2017.  While large enterprises invest billions to  develop machine learning (ML) capabilities, smaller companies and individuals can sometimes feel that machine learning is out of their reach. After all, the average salary for a machine learning engineer is about $140,000/year (source), and learning how to code isn’t exactly a small task.  Luckily, one emerging technology trend, machine learning as a service (MLaaS), is removing barriers such as time, budget, and even coding expertise to make the power of machine learning available to everyone. Offering ready-made tools that can be easily adopted and fitted to various business needs, MLaaS is being used by business leads and front-line workers in an array of industries. So how does MLaaS work? No code needed: basic features of democratized machine learning Coding expertise is perhaps the largest barrier to creating apps. Software development traditionally includes everything from data collection and debugging to resource provisioning and security, which is (for good reason!) a full-time job in and of itself. Machine learning applications are no different, and require a foundation of complex coding before app development can begin.  No-code development platforms automate the bulk of this sophisticated behind-the-scenes work so that non-technical users, aka citizen developers, can tackle the business task at hand without touching a line of code. This means that teams and individuals can autonomously build and deploy apps made by them — and for them — in a matter of days, not months.  Whereas traditional models of app development require heavy cross-functional communication and weeks of iteration, no-code development puts the power to solve problems into the hands of those who know the problem best. Because no-code requires zero technical know-how, MLaaS is accessible to a much wider group of people and teams within an organization than traditional machine learning implementation.  With a no-code platform, anyone — regardless of their technological prowess or background — can build robust applications that are driven by machine learning algorithms to solve problems, increase productivity, and deliver a healthier bottom line. MLaaS and the power of problem-solving Like no-code development, MLaaS is not limited to any particular group, and is used by industries from manufacturing to healthcare to empower non-technical employees to improve their processes with powerful digital technology. Faster time-to-value: Business leads and process owners often know best where help is needed on the ground, but can’t wait weeks or months for diverse teams to coordinate, build, test, and iterate on a niche application built with them in mind. MLaaS makes it easy for process owners to build apps that do everything from helping users interact with data more quickly through natural language processing to interpreting qualitative categories of new data, within days. Process improvement: MLaaS can also help non-technical process owners significantly streamline workflows and existing processes. For example, MLaaS empowers any employee to build predictive models that can generalize from historical app data, providing the ability to forecast values and predict trends. Time reallocation: From supply chain optimization to inventory management and predictive maintenance, businesses rely on software development and machine learning to get things done. When the power of machine learning is distributed across an organization, the role of planning and execution moves from the IT and development teams, to the  people who know their challenges best. This frees up time for IT teams without sacrificing technical ability and growth. Tools that put experts in control As we’ve seen, MLaaS allows anyone in an organization to digitize routine work and automate tasks with apps that would have otherwise been too costly or time-consuming to develop. From HR and finance to sales and marketing, people in any area of a company can easily build apps that are customized for their team, process, data, and goals.  With no-code, machine learning doesn't need to be expensive to deliver enormous value. This democratized solution saves companies time, money, and resources, while empowering every employee to do her best work. AppSheet machine learning resources Create apps on AppSheet with the power of machine-learning built in. Exploring these resources to learn more:  AppSheet Intelligence features page White paper: Why the Future of Machine Learning is No-Code Ready to start building no-code apps on AppSheet? Sign up for free today:

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