In some ways, artificial intelligence (AI) and agility form part of a lifecycle: businesses need to be agile to introduce disruptive tech like AI, whilst AI in turn can help businesses achieve true agility.
As difficult as the disruption of the past year has been, it has undoubtedly been a driver for businesses to get their priorities straight. The effects of the global pandemic have clearly distinguished between those organizations that are agile and proactive, and those that are not. The latter group has generally found it much harder to cope with market disruptions and will continue to struggle to seize new opportunities.
Chris Pope is VP Innovation at ServiceNow.
According to IDC, there are five key pillars required to achieve organizational agility: leadership vision, structural agility, process agility, portfolio agility, and technology architecture. Undoubtedly, ‘human’ factors play just as significant a role in forming agile businesses, when leaders look beyond budgets and conventional measures of profitability to shift towards human-centric metrics, like talent, skills, and employee experience. Agile companies benefit from the ability to quickly evolve and adapt to demand and emerging patterns, both internally and externally.
Agility also enables organizations to constantly introduce disruptive technologies. From a tech perspective, however, many believe that agility in its current form begins and ends with remote working tools. Yet in reality, truly agile organizations run on integrated digital platforms that provide transparency into the business and its operating environment. Adding artificial intelligence into the mix can take the approach one step further, creating benefits that can help organizations embark on their journey to agility.
The business benefits of AI
The AI opportunity for businesses has been widely covered, with the technology expected to deliver a 22% boost to the UK economy by 2030, according to McKinsey. However, successful implementation relies on an organization's ability to understand its capabilities and scale successfully.
There are numerous use cases of AI that show a tangible impact on agility. The technology’s unique ability to provide critical insights delivers efficiencies in many layers of company operations, from decision-making to customer service to product design, in turn increasing productivity. In fact, Gartner predicts that this year, AI will create 6.2 billion hours of worker productivity globally, resulting in $2.9 trillion of business value.
AI’s predictive analytics skills combined with immense computing power significantly streamline and accelerate the speed and accuracy of decision-making. In some cases, this involves quickly capturing, analyzing, and presenting the relevant data, along with a recommendation on the next steps. It can even go as far as making decisions itself, something we will begin to see more of as the technology continually matures. As machines possess the ability to process inputs mathematically with unprecedented speed, and make decisions based on previously accumulated data, the resulting outputs are highly accurate, eliminating the risk of human error. This speed of accurate decision-making leads to quicker resolutions, enabling the agile business to identify and fix problems before they even begin to develop.
Deployment also offers vast potential for cost reduction. Businesses investing in AI see savings from the automation of menial jobs, process improvement, and reduced errors. These efficiencies prove invaluable in unique ways for different sectors. In retail, for instance, the use of AI presents a $300 billion cost-saving opportunity alone, helping retailers manage customer complaints, automate procurement tasks and optimize supply chain route plans.
Ultimately, humans will never be able to work 24/7. AI can work continuously without breaks or dips in productivity, consistently providing the same quality of service. In this way, it can help organizations reach levels of agility that would have been previously unattainable without the use of technology.
The AI implementation
Through smarter decisions, quicker resolutions, reduced costs and minimal errors, it is clear how AI can improve agility. But there are steps organizations should take to effectively implement this technology. In some ways, AI and agility form part of a lifecycle: businesses need to be agile to introduce disruptive tech like AI, whilst AI in turn can help businesses achieve true agility. Laying out the initial groundwork will prove invaluable in embarking on the journey of adoption.
Organizations should first identify and agree the problem to be solved. Every business has areas that could be improved or processes that would benefit from becoming more productive. Establishing these inefficiencies will allow organizations to better determine AI’s use cases and see the long-term advantages.
Businesses will also need to understand their internal capabilities, looking at their existing people, technology, and data. Implementing new tech does not necessarily require a complete overhaul. Many modern solutions slot cohesively into the existing technology stack, enhancing existing process and providing new capabilities on top.
When implementing AI, starting small enables organizations to prove the model and the outcomes before expanding to other areas of the business. The agility journey is a marathon, not a sprint. Successful digital transformation is an important step, but improving culture, structure, skills, employee experience, and attracting and retaining talent are equally as vital.
Whilst AI can quickly deploy functional outcomes, other technologies can also help to improve business agility, such as Robotic Process Automation (RPA), Business Process Management (BPM), Orchestration and Analytics. Organizations should consider all available options and how they can work in tandem, complementing each other for the most suitable, tailormade approach for the business. With technology, there is no one size fits all, and a combination of digital capabilities can transform the overall experience.
The route to agility
Whilst organizations cannot solely rely on AI to help them become agile, businesses can use the tech to resolve many of the pain points currently holding them back. Its data insights drive better decision-making, it can fix issues before they escalate, and it reduces costs, all while maintaining consistent and continuous service delivery.
Technology, people, culture and structure form the essence of the ‘Operating System of the Enterprise’. Those businesses who maximize the potential of each pillar will discover and accelerate their route to achieving agility, reaping the benefits as a result.
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