By Lara Fox, MD, Objective
With all the support that AI can offer, it has quickly become a helpful tool for decision makers, increasing its implementation to businesses by 145% over past ten years.
Recent research also shows that 1 in 6 organisations have already adopted AI technology, with 79% of people choosing to use AI to help them at work. AI solutions allow organisations to gain insight that can help enhance overall business performance and capability.
The benefits of AI are continual, and when applied correctly within organisations it can provide substantial support with customer insights, personalisation, operational efficiency, automation of processes, and sales. It can also act as an integral tool when it comes to understanding customer behaviour and market conditions.
How can business leaders implement these tools
The power of AI is its ability to analyse vast amounts of data quickly, enabling businesses to extract valuable insights from text and speech, automate customer interactions and conduct sentiment analysis as just a starter for ten. It can also help businesses automate tasks, boost productivity, enable data-driven decisions with deep insights and ultimately unlock new opportunities. Machine learning models can also be built to analyse historical data to forecast trends, detect patterns, and generate actionable insights.
AI can work faster than traditional processes, cutting out valuable business time and allowing employers to focus on other tasks. Data analytics also allow business owners to see patterns emerging and spot trends. The data insights can then be used to gain further knowledge into clients and customer behaviour which can then be used to boost sales and personalise marketing efforts.
A popular AI option that can drive sales for many businesses is looking at the open and click through rates for their marketing emails to estimate the best times to send communications to each specific business audience. This allows business owners to craft segments in marketing data by using machine learning and Natural Language Processing (NLP). This supports with customer feedback from social media, reviews, and surveys to help better understand and identify areas for improvement.
Streamlining financial processes
Tasks like bookkeeping, payroll, invoices and expense management can all be automated through AI. By streamlining repetitive tasks, organisations will save time allowing team members to focus on more strategic tasks. Application Programming Interface (APIs) can also connect different systems together such as Xero or Salesforce enabling the systems to share data and perform analytics to produce valuable data insights. Taking this another step further, businesses can use data analytics to spot errors or inconsistencies in the data being automatically transferred between programmes, saving businesses both time and money.
Enhancing forecasting ability
AI can use historical data to aid with forecasting trends, customer behaviour and market changes with greater accuracy. Installing Machine Learning (ML) to databases and web apps used for forecasting allows algorithms to forecast information and enhance inventory management. In addition, ML can also be used to forecast demand and optimise inventories. This is not only for large businesses; Microsoft’s ‘Azure Auto ML’ can run 50 machine learning models on data without needing a single line of code making it accessible for SMEs too. It can be linked with Power BI to produce dashboards which allow business owners to review the data and use it for reporting. Machine learning, data sets and intelligence together can help towards making data-driven decisions.
Consolidating supply chain management
Trend data from machinery and equipment can support businesses by helping to predict the lifespan of equipment, identifying failures before they occur. And in addition, reducing downtime and maintenance costs. Real-time data and algorithms can also help with supply chain optimisation, predicting disruptions and finding any areas of inefficiency or concern. This can decrease the risk of wasting any unnecessary resource. Power BI can also help here by tracking the flow of goods, as well as finances and any additional information across the supply chain which can help businesses with identifying ways to help with operational performance going forward.
Implementing seamless logistics and time management
Route planning can be delivered using AI technology, taking data from databases and IOT devices such as sensor data which helps automate allocations. AI development can reduce manual work and maximise resource allocation through intelligent automation. This process can also be made more seamless as the automated timesheet retrieval and job allocation data can be collected and held together on one single report. It can also be used for logistics coordination, allocation of resources and distribution of team members. Moreover, businesses can use this for quality control and implementing validation systems to help maintain consistent accuracy.
Using data analytics and AI for business success
The lack of understanding around AI by businesses is still a barrier to entry for some. Technology moves at such speed that it can be difficult to keep up and its this that seems to hold many businesses back from adoption. With so many options to choose from, it can be difficult to understand what the tools can be used for, however, when the time is taken to gain the knowledge around these solutions it could be hugely beneficial and support long term business objectives.
Having the ability to able to use the data combined with other digital tools allows business owners to gain a true view of where their business is at and how it can be streamlined to become more efficient, to keep evolving, continue to improve and stay ahead of the competition.
