Seemingly, not a day passes without a news story featuring a major organisation proclaiming the enhancement of their AI capabilities, debates on the tech’s ethical implications, or claims that AI art will have a lasting impact on culture.
However, for businesses, the tangible, real-world solutions offered by AI are substantial. Following a rapid period of digitalisation prompted by the Covid-19 pandemic and subsequent years of economic uncertainty, AI has emerged as a much-needed boost—a metaphorical extra pair of hands, addressing critical business needs.
With much of the focus around the adoption of AI by industry giants such as IBM for example, whose recent 4% increase in revenue was propelled by the demand for AI products and services, it's essential to recognise that small businesses, disproportionately impacted by economic turbulence, are also taking notice. According to a recent study by Small Business Britain, over a third (38%) of small enterprises have either adopted AI or are contemplating its integration into their operations.
AI has the potential to benefit businesses of all sizes, but it is up to each business to assess which form of AI best aligns with their unique needs.
The many forms of B2B artificial intelligence
In order to optimise their processes and meet their goals, it is imperative for businesses to pick the right AI solutions. AI has many faces, from natural language processing (NPL) to machine learning and computer vision, and the onus is on decision-makers to pick the right one according to their needs.
ChatGPT may hog the headlines, but other generative AI platforms have the potential to transform the way business approach communications – especially SMEs. The ability to generate text for marketing content, reports, and both internal and external communications can streamline the content creation process, curtailing the time spent on producing and reviewing multiple drafts.
Chatbots are another solution that are impacting both B2B And B2C enterprises. NLP makes communication between humans and machines more natural and interactive, enabling greater B2B lead generation. Chatbots and virtual assistants equipped with NLP capabilities can participate in meaningful conversations with potential leads, evaluating them based on nuanced interactions.
Indeed, recent research from RSM indicates that 53% of middle-market business leaders believe that generative AI has the potential to enhance customer engagement, with 60% anticipating an overall productivity boost through its implementation.
Cutting-edge generative AI platforms are currently showcasing their prowess in deal management and business advisory services, playing a vital role in facilitating the scalability of companies. These platforms leverage information stored in databases containing potential clients, suppliers, and financial advisors. Through categorising the strengths and expertise of individuals, they efficiently identify matches that align with specific business needs. The rapid identification of contacts speeds up establishing connections and fostering relationships.
Another crucial facet of tailored AI products is their capacity to deliver sophisticated analytics that enhance strategic decision-making. Using machine learning algorithms, these systems meticulously examine extensive datasets, extracting valuable insights that empower businesses to make well-informed decisions. This includes forecasting market trends, identifying potential risks, and comprehending customer behaviour. The application of AI-driven analytics streamlines decision-making, mitigating uncertainty and enhancing overall operational efficiency.
Additionally, the swift decision-making empowered by advanced AI tech is now reaching beyond initial concepts, turning futuristic ideas like self-driving cars into highly efficient reality. Consider airport safety as an example:
In addressing safety concerns within airports, AI systems can seamlessly integrate with surveillance cameras, leveraging real-time monitoring technologies. By harnessing computer vision to differentiate between luggage and potential safety issues, these systems enhance safety measures without compromising operational efficiency.
For instance, in ensuring child safety on luggage carousels and conveyor belts, AI technology can be deployed to detect unusual scenarios. The moment a safety concern occurs, it's quick to act— triggering alarms or temporarily halting the conveyor belt. Of course, these capabilities extend beyond the airport, offering customised setups for authorised personnel to prevent false alarms based on confidence levels.
A tailored approach
In adapting AI applications, the focus for businesses should be to unlock their potential by seeking bespoke AI solutions that not only boost productivity but also contribute to increased profitability.
By collaborating with developers, who can understand the intricacies of a client's operations and overarching goals, business leaders can ensure products are the right fit for their processes. This collaborative approach ensures that the developed AI solutions are not just technological innovations but strategic assets that contribute to the client's long-term success.
When it comes to business operations, there is no one-size-fits-all approach; the path chosen depends on the unique characteristics of the business and its clientele. However, any company neglecting to prioritise its technological advancements risks losing ground to competitors that provide a more seamless and sophisticated experience to their clients.
It's not just about the buzz surrounding AI; it's about translating the potential into tailored, pragmatic solutions that propel businesses toward newfound efficiency and success. While AI reshapes industries, sparking both excitement and scepticism, its tangible impact on businesses remains undeniable. Whether it's major corporations or small enterprises, the uptake of AI is on the rise, marking a shift in business operations, and the ongoing boost from tailored solutions is set to persist.
Ritam Gandhi is the Founder and Director of Studio Graphene.
