The importance of deploying AI correctly
Businesses recognise the potential of artificial intelligence (AI) deployment. IDC estimates that USD$35.8bn was spent on AI in 2019.
However, some companies are struggling with AI because they are taking half measures, only implementing them in small use cases or in environments where the data is insufficient to power its success. That’s causing their businesses to flounder.
Enterprise AI isn’t something that businesses can dip their toes into. Companywide buy-in and methodical planning ensure that one’s eyes aren’t too big for his stomach. According to PwC, AI has the potential to contribute $15.7trn to the global economy by 2030 and boost GDP for local economies by as much as 26%.
Yet, return on investment is directly correlated with the sophistication of the AI deployment. Successfully implementing AI requires that companies think big—and with long-term goals in mind.
Operating a 24/7 business
Take for example a business that needs to operate 24/7. There are many challenges and expenses associated with round-the-clock, particularly multi-market service. The biggest one is the struggle to acquire enough talent to be in the office at all times. That’s why most businesses limit many services within a single time zone. But in this constantly connected world, where clients and customers expect assistance at any moment, the need for an always-on solution has never been more pressing.
Cognitive AI—that is AI capable of “learning” over time—is able to turn any business into an always-on and always ready entity. By drawing on organizational data, cognitive AI is able to answer customer questions around the clock and handle typical high-volume but low-value tasks with little to no human involvement. This allows customers from around the world to engage with the business whenever it is most convenient for them and substantially reduces the strain of providing 24/7 service on human employees.
According to McKinsey, 45% of workplace activities which currently rely on human intermediation could be replicated by machines and therefore, be executed with machine efficiency. That isn’t to say that humans would be replaced, however. Humans will still be central to identifying the tasks necessary to achieve a result, and they would be responsible for building the workflow based on those tasks, but AI can build the automation that transforms how business is done.
Previously, the only way to create automation that addressed a company’s unique needs was to have a dedicated team of engineers research business processes and then identify and describe all necessary steps to reach a resolution
With intelligent automation, however, systems can combine analytics, cognitive AI and guided machine learning to hasten the creation of new automation. Without having to execute the entire process themselves, the human staff can spend more time on the work that adds value, such as conceiving new products and services or improving the customer journey.
Making the right investment
It is not an exaggeration to say that AI will revolutionize the enterprise and bring a wealth of financial and productivity gains. Its promise makes it an unavoidable line item for any business hoping to compete in the global economy. But, like any investment, if it is poorly implemented, it will be high-risk, costing companies so much in the long-term.
This article was contributed by Chetan Dube, CEO, IPsoft
Intelliwave SiteSense boosts APTIM material tracking
“We’ve been engaged with the APTIM team since early 2019 providing SiteSense, our mobile construction SaaS solution, for their maintenance and construction projects, allowing them to track materials and equipment, and manage inventory.
We have been working with the APTIM team to standardize material tracking processes and procedures, ultimately with the goal of reducing the amount of time spent looking for materials. Industry studies show that better management of materials can lead to a 16% increase in craft labour productivity.
Everyone knows construction is one of the oldest industries but it’s one of the least tech driven comparatively. About 95% of Engineering and Construction data captured goes unused, 13% of working hours are spent looking for data and around 30% of companies have applications that don’t integrate.
With APTIM, we’re looking at early risk detection, through predictive analysis and forecasting of material constraints, integrating with the ecosystem of software platforms and reporting on real-time data with a ‘field-first’ focus – through initiatives like the Digital Foreman. The APTIM team has seen great wins in the field, utilising bar-code technology, to check in thousands of material items quickly compared to manual methods.
There are three key areas when it comes to successful Materials Management in the software sector – culture, technology, and vendor engagement.
Given the state of world affairs, access to data needs to be off site via the cloud to support remote working conditions, providing a ‘single source of truth’ accessed by many parties; the tech sector is always growing, so companies need faster and more reliable access to this cloud data; digital supply chain initiatives engage vendors a lot earlier in the process to drive collaboration and to engage with their clients, which gives more assurance as there is more emphasis on automating data capture.
It’s been a challenging period with the pandemic, particularly for the supply chain. Look what happened in the Suez Canal – things can suddenly impact material costs and availability, and you really have to be more efficient to survive and succeed. Virtual system access can solve some issues and you need to look at data access in a wider net.
Solving problems comes down to better visibility, and proactively solving issues with vendors and enabling construction teams to execute their work. The biggest cause of delays is not being able to provide teams with what they need.
On average 2% of materials are lost or re-ordered, which only factors in the material cost, what is not captured is the duplicated effort of procurement, vendor and shipping costs, all of which have an environmental impact.
As things start to stabilise, APTIM continues to utilize SiteSense to boost efficiencies and solve productivity issues proactively. Integrating with 3D/4D modelling is just the precipice of what we can do. Access to data can help you firm up bids to win work, to make better cost estimates, and AI and ML are the next phase, providing an eco-system of tools.
A key focus for Intelliwave and APTIM is to increase the availability of data, whether it’s creating a data warehouse for visualisations or increasing integrations to provide additional value. We want to move to a more of an enterprise usage phase – up to now it’s been project based – so more people can access data in real time.