“Alexa, list all of the hot technology trends for 2019.”
…well, maybe I still have to come up with that list…for now. The pace of technology innovation continues to accelerate, and companies continue to find navigating the business strategy, business model, workforce, customer interaction, and business operational changes necessary to compete effectively to be a significant challenge. This progression will continue through next year and beyond.
Digital Transformation Trends 2019
We started “talking” about digital transformation (DX) over a decade ago. In the naivety that was 2008, many believed that the journey was just about technology and had a beginning and an ending—at least one that would come before 2018.
We’re now in the second generation of DX. I like to think we’re finally starting to see that technology is the foundation of this journey, and a business still has to go through an entire transformation that includes business strategy, business model, workforce, customer interaction, and business operations.
The second generation of DX is focused on the business as a platform that enables agile and flexible global operations. The companies that are the most competitive and have the best chance for long-term survival are able to build and maintain a business strategy that can adapt to changing business and technology conditions.
The modern business platform has a technology or digital core that supports the ability to build and adapt a digitally enabled business model. This model addresses the way the business goes to market, the way it supports its workforce, and the way it produces its product(s) and service(s). More and more, for digitally savvy businesses, the technology is so intertwined with the model and the operations that they aren’t easily separated, which supports the concept that a business is an integrated platform—or at least should be.
For 2019 and beyond, the following five trends are the most powerful and support the continued expansion of DX:
- Artificial Intelligence (AI) / machine learning (ML) platforms are embedded in the business platform, rapidly enabling “smart” business operations.
- Blockchain continues to expand “out” of cryptocurrency transaction management and becomes a part of the core business platform, enabling transactional transparency across a wide variety of business functions.
- Internet of things (IoT) adoption among mid-market and enterprise businesses accelerates as more IoT platforms are available to enable the actionable and secure application of IoT sensors to high-value business issues.
- The majority of enterprise businesses adopt a cloud platform from one or more providers and accelerate the shift back to “custom,” microservices-based, industry vertical-specific solutions over “off the shelf” SaaS.
- Conversational UIs becomes the pervasive method for interacting with enterprise systems for workers and customers.
These five technology trends are not new, but the level of use and adoption is taking a significant upswing from momentum that was created over the past couple of years. This adoption is also expanding across the entire set of business functions and activities, partially based on availability and solution maturity, and partially based on increasing business pressure to change. Let’s take a deeper look at each of the trends:
Artificial intelligence and machine learning
AI/ML platforms are embedded in the business platform, rapidly enabling “smart” business operations. There are two basic approaches for AI/ML platforms that are available to businesses today. There are standalone AI platforms that allow businesses to build ML algorithms for nearly any conceivable application, and embedded AI platforms that function inside a specific application or process. At a very basic level these platforms can automate a task or set of tasks (processes) or analyze a data set to provide either a decision or a set of actionable insights that support a human’s decision process. The algorithms themselves tend to function in two types of outcomes: either a scenario that has a specific “answer” or decision, or a scenario that is open loop and requires the algorithm to continuously iterate to get to an outcome. The second situation, which is a branch of ML called reinforcement learning, provides algorithms that take context into account to maximize behavior inside the scenario.
There appear to be an endless number of use cases for AI/ML. Sales personnel can be more productive and effective by using AI-enabled sales intelligence tools to get real-time contextual information on prospects and customers. They can also use a scheduling bot to manage calendaring and appointments. Customer service representatives can improve customer interactions by using AI-powered customer service systems that recognize customers, provide contextual case and transaction information, and support the agent in solving issues and knowing what new products and services would be the best offer for the customer. Project managers can get proposed staffing plans based on real-time resource assignments based on skills and capacity and project plans that use both historical data and project context to build accurate project plans. There are many more examples that range from tools that make workers more productive, to tools that interact with customers form a highly improved experience or even autonomous delivery vehicles.
Blockchain continues to expand “out” of currency transaction management and becomes a part of the core business platform, enabling transactional transparency across a wide variety of business functions. Almost any decentralized transactional process can benefit from the use of blockchain ledgers. The blockchain ledger simply provides a highly verifiable method for recording and tracking anything without a centrally located guarantor. (Blockchain is already being used from “smart” contracts in procurement, for example.) Any financial transaction would be a candidate for the use of blockchain. In HR, blockchain ledgers are used in payroll, particularly for third-party contract employees. Beyond that, it is being applied to recruiting challenges like ensuring someone has the credentials and experience they claim. Blockchain as a service offerings are hitting the market to facilitate companies building unique blockchain applications. Many application vendors are embedding blockchain into specific applications as well.
IoT adoption among mid-market and enterprise businesses accelerates as more IoT platforms are available to enable the actionable and secure application of IoT sensors to high-value business issues. IoT has been a hot topic for many years but adoption has never lived up to projections. There are several reasons for this. Security is certainly a big concern and has probably made some companies hesitant. The lack of standards and its subsequent contribution to the overall perception of complexity surrounding IoT is likely another factor. Projects are also challenged by the lack of skilled and experienced resources, which at best has slowed down many initiatives and at worst hampers the ability to develop coherent project proposals. Without the right resources, the “unknown unknowns” create the perception of high risks.
The availability of more IoT platform and device choices, coupled with the increasing number of resources, is finally starting to turn the reluctance around; many new projects are finally underway. This trend will accelerate across the next five years, with companies building on successes internally and across competitive communities. There’s a lot of unlocked value on the horizon, which should become obvious as more companies jump into the game.
The majority of enterprise businesses adopt a cloud platform from one or more providers and accelerate the shift back to “custom,” microservices-based, industry-vertical specific solutions over “off the shelf” SaaS. I suppose there’s a lot to unpack in this trend, so let’s start with the platforms themselves. Cloud infrastructure (IaaS) and platforms (PaaS) use is extremely widespread, although the use varies greatly from company to company. In the enterprise at least, more IT shops are dealing with a hybrid on-premises or cloud application environment. The platforms offer the way to move workloads to the cloud, extend SaaS and on-premises apps, integrate across the hybrid environment, and increasingly build company-specific apps. However, companies in general seem to be using more than a single vendor. This is not necessarily to prevent vendor lock-in, but more to leverage strengths of different platforms and existing relationships. It’s likely that many IT shops will start to focus on one or two vendor offerings as they become more invested in the uses and more sophisticated in their operations.
The second part of the trend—that companies are increasingly building apps over buying—is a little more complex. There’s quite a bit of history around the build versus buy argument, and over the years momentum has moved back and forth. A lot of the momentum was related to platform factors, as well as ability and complexity of execution. Historically, software vendors, particularly horizontal app providers, built apps that would meet some requirements across a wide range of companies. They would probably claim that the fit was approximately 60–70% before configuration and customization. In reality, the fit was usually much lower than that estimate, and the work to make products provide value was high. Getting to the 80% mark was often painful. Today, with rapid development platforms and much more complete IaaS and PaaS offerings, it is becoming more common for companies to extend existing apps and to construct best practice apps that meet nearly all the company’s requirements. To just say companies will build more than buy is probably a bit of an overstatement, though. I believe that the combination of both make more sense. There are common processes and systems that should probably be mostly buy, especially in core business functions like finance. Outside that common core though, especially in processes that vary greatly by industry, building is probably the better choice for most companies.
Conversational UIs become the pervasive method for interacting with enterprise systems for workers and customers. In our personal lives, we have become very comfortable with the idea of conversational interaction with a variety of systems ranging from mobile devices to thermostats to automobiles. It’s a very natural way to interact with systems, both with voice and chat. Customer service systems have made wide use of bots as a way to effectively interact with customers and improve service levels. Devices like Amazon Alexa and Google Home could see use in businesses. More likely, though, companies will look to systems like digital adoption platforms (DAP) that can sit on top of existing business systems and provide a variety of conversational interfaces for employees. It’s also likely that more systems will simply offer chatbots and voice interfaces natively. Many of the IaaS platform providers are providing access to bot and voice platforms. AWS, for example, provides the underlying platform used by Amazon Alexa as a service, or Alexa for Business.
There are other trends that I didn’t list of course, many of them covered by our G2 Crowd buyer research team. Here’s a summary of the other trends for 2019:
AI, Big Data, and RPA
AI trends: Machine learning as a service (MLaaS), robotic process automation (RPA), and machine learning data catalogs (MLDCs) are becoming necessities to businesses that are embracing the data-driven business world. Their impact will only continue to grow in 2019.
Agtech trends: Like any other industry that’s transformed by tech, the agriculture space must keep up with changing work styles, updates in equipment and mobile devices, and the demand for speedy results. Agtech trends will be heavily influenced by millennials in 2019, and will have the biggest impact on small farms.
AR/VR trends: Virtual reality (VR) has been on the outskirts of technology for years, but has been inching toward breaking the barrier into the mainstream. However, augmented reality (AR) has been quickly rising in VR’s shadow. AR technology is set to outpace VR’s growth drastically in the next few years.
Cybersecurity trends: As every industry adapts to new and emerging threats, 2019 will see increased focus around the “zero trust model,” biometric authentication, IoT security, and information compliance technologies.
Content management trends: Businesses have always been concerned with team cohesion and effective, efficient content marketing. In 2019, their efforts will turn toward increased adoption of productivity tools, less conventional web content management systems, and artificial intelligence in content creation.
ERP trends: In the near future, ERP buyers and vendors will need to adjust their strategies to adapt to the new reality of pervasive automation. Traditional software is starting to be replaced by RPA, and the transition from old to new technology—as well as increasing economic instability—will make companies realize that governance software and services are more than a necessary evil.
Fintech trends: Fintech is transforming the financial services industry, and will continue to do so as the industry makes the shift to fostering innovation. In 2019, fintech will be bolstered by RPA, mobile banking, insuretech, open banking, smart contracts, and more.
HR trends: The HR technology trends that will have the biggest impact in 2019 include solutions that will promote employee engagement, diversify companies, rethink sexual harassment training, expand corporate wellness solutions, and employ AI to improve HR operations.
Retail, Restaurant, and Hospitality
Retail trends, restaurant trends, and hospitality trends: Retail, restaurant, and hospitality are all spaces set to see huge technology gains in the year to come. Between omnichannel and e-commerce in retail, mobile payments in restaurants, and AI personalization in hospitality, 2019 is set to see huge improvements in these customer-facing industries.