It’s the battle of the machines! And while the concept of AI may conjure up bombastic visions of terminators, replicants and space odysseys; in the modern business world, Artificial Intelligence has become a regular part of our everyday lexicon. Now, topics like implementing smart automation, machine learning, facilitating support via chatbots, gaining insights with predictive analytics, etc., are all somewhat recent AI-based innovations that have changed the conversation around business process and operations.
Augmenting and automating business and IT processes are the key benefits for organizations to get those most out of AI and smart-enabled applications. However, what’s really interesting is how these platforms have given Small and Medium-Sized Businesses (SMBs) a competitive edge against some of their bigger, monolithic enterprise counterparts.
Read more about how AI, chatbots, machine learning and other smart technologies are changing the competitive landscape for small and mid-size businesses.
Doing More With Less
Automation is one of the biggest strengths of Artificial Intelligence, and leveraging AI services to quickly automate routine and repetitive tasks has revolutionized the modern workplace. With the assistance of AI-powered applications and services, SMBs can operate like a fully-staffed global enterprise company, with the added benefit of more speed and efficiency. Business tasks like scheduling meetings, setting up business development workflows, booking flights and hotels, answering low-level service requests and performing routine clerical work can now be automated with less manpower at a higher efficiency.
TechCrunch writer Michael Yamnitsky compared this rise of transformative AI-powered applications for the business world to what happened in the early 90s for insurance claims processing and other mundane tasks thanks to the proliferation of IT systems and modern computing. As this trend continues, SMBs will find more ways to do work efficiently with less resources, putting them on the same wavelength in terms of process with larger companies, while also working leaner and without spending as much on overhead costs to keep operations flowing.
Enabling Proactive Services
As AI becomes the norm for enterprise services and business processes in general, the trend we’ll begin to see in process and operations is the shift from a simple reactionary methodology to proactive services that work ahead of time. IT makes one the strongest use cases in this respect. For instance, predictive analytics (powered by machine learning) offer insight into future trends for service desk operations. These charts and graphs offer a prophetic look into the future, allowing teams to identify problematic areas within their process or organizational environment so they can act before trouble begins to occur.
Being proactive is also the driving force behind AIOps, which Gartner describes as: “platforms that utilize big data, modern machine learning and other advanced analytics technologies to directly and indirectly enhance IT operations (monitoring, automation and service desk) functions with proactive, personal and dynamic insight.” AIOps essentially takes all the tools, configuration components, data sources, and automations that make up the IT infrastructure, and adds a layer of intelligence to it. This allows organizations to get a clearer picture of their operations and identify potential problem areas, triggering alert automations so they can work proactively to keep things running smoothly. Unplanned service downtime can significantly hurt or even cripple SMBs, and these proactive measures are just another means of safeguarding them from disastrous outages, while also helping them to solve problems before they get out of control.
Doing More With Data
While automation is a key part of AI’s disruptive force on the business world, that’s only telling part of the story. Big data, analytics and smart Business Intelligence (BI) is arguably more transformative for its ability to shed insight, predict trends, and track performance in real-time. In IT for example, the aforementioned predictive analytics dashboards allow teams to get insight into whether or not they risk violating any SLAs in the next three months, gauge end user sentiment over time, or are on pace to meet their incident close rate goals based on performance.
Additionally, AI and Machine Learning enhancements have allowed SMBs to make better use of their historical data, efficiently operationalizing it so they can squeeze as much value without turning to costly data scientists. For example, smart recommendation engines can be used within an incident ticket to provide contextual guidance for each form field based on the IT organization’s own ticket history data. This allows help desk operators to fly through ticket completion while also minimizing mistakes and providing the most accurate assessment of how the ticket should be managed (i.e., closed, escalated, prioritized, routed, etc.).
Delivering More Engaging Customer Service
Perhaps the hottest segment of the space that leverages AI-powered business applications would be those that deal in customer service. Chatbots and virtual assistants are helping to engage customers while also automating first-tier support and taking some of the workload off support staff resources. And while AI is not a true replacement for human engagement, it can act as more efficient first-touch contact, where end users can quickly describe their issue and get solutions via a bot’s Natural Language Processing; all without going through the process of submitting a support ticket.
Chatbots are a huge benefit to SMBs that are looking to provide the best customer service possible on a limited budget and with less resources. They are a great way to promote engagement of self-service systems rather than take up the time and energy of an in-house staff member.
With the support of turnkey cloud solutions and AI-powered applications, the playing field has inched closer to a more even plane between large enterprise companies and SMB organizations than ever before. As new innovations come to market, small and mid-size companies will find new and better ways to work more efficiently without spending an arm and a leg on process and making better use of internal staff resources.