Artificial Intelligence in companies, why use it?
Most likely, the cloud will be one of the priorities in their investment plans in key technologies for this year because the use of Artificial Intelligence in companies is becoming increasingly widespread.
Cloud investment continues to grow, and 75% of information technology (IT) leaders are investing moderately or significantly in the cloud, according to a new KPMG survey.
If you are contemplating investing, you have identified specific uses for applying or experimenting with transformative cloud-powered solutions. One of those solutions should be Artificial Intelligence (AI).
In particular, Artificial Intelligence for conversational intelligence, automation of robotic processes, analytics and knowledge.
Adopt Artificial Intelligence in companies analytically
Companies that use next-generation technologies like AI effectively see increased customer centricity, revenue growth, and employee satisfaction.
KPMG, for example, found that digital leaders—companies that improve customer experience and operational performance through stable and scalable transformation—are 2.5 times more likely to invest in robotic process automation. Overall, 17 percent have made significant investments in AI, compared to just 5 percent of companies on average.
Invest in new forms of digital operations based on AI
What is important is that digital leaders are more likely to invest in this technology class and are reaping the benefits. Consider the big companies devoting huge resources to AI: Google ($3.9 billion), Amazon ($871 million), Apple ($786 million), Intel ($776 million), and Microsoft ($690 million). Dollars).
Even among companies that don’t invest such a large amount of resources. Studies show that 46 percent are already seeing a boost in revenue when using Artificial Intelligence in their customer service operations.
This profitability is the result of proven demand, and our research indicates that 60 percent of consumers are open to advanced technologies such as Artificial Intelligence.
The demand and the return are there. So why are most companies delaying investment? That is Pandora’s box that I will try to open in this informal guide to Artificial Intelligence.
What prevents companies from investing in Artificial Intelligence?
At this point, there is little doubt about the security and resistance of Artificial Intelligence. Among the significant obstacles to further adoption, today are a lack of alignment with the company’s business, immature or outdated technologies, and a devastating shortage of trained staff.
Nearly 70 per cent of CIOs surveyed by KPMG cite a lack of skills as one of the reasons that prevent the company they work for from keeping up with changes. While 55 per cent rate the alignment between their IT department and the company’s business as “moderate” or worse (our studies also find disparities between IT and lines of business in terms of ownership of transformation).
Ideas to adopt the techno
The difficulty in crafting competent, industry-specific AI solutions is part of this problem.
Sound familiar to you? It is what you should start doing to achieve improvements:
Be creative when selecting your employees:
Digital leaders know that any strategy is incomplete unless it has the right people to execute it. It is not a terrible idea to bring in outside companies and consultants while evaluating internal candidates (85 percent of companies are doing this, according to KPMG).
Outsourcing can be beneficial for experimenting with AI development and testing. The goal, however, should be to close the skills gap for a long-term and sustainable transformation.
People are the fabric of what a company does every day. Artificial Intelligence is necessary for continuous growth and innovation, but people are the engine behind its mission and vision. Understanding this is a common thread that unites all digital leaders today.
To close the skills gap, IT leaders must be willing to broaden their horizons and spot new possibilities. It has recently explored this concept in depth, particularly concerning people and culture.
Think hard to assess the level of IT and alignment with the business of the enterprise (LOB):
IT leaders should ask themselves key questions, such as which departments in the company are (or should be) responsible for AI initiatives and which should be the main drivers of such initiatives. Identify the objectives of the Artificial Intelligence projects carried out by your company and the desired impact of such projects on each of these objectives.
I recently proposed four steps to reposition IT and LOB for transformational success, which can be applied to AI initiatives.
Begin the transition from proprietary technology to automated software architecture:
So much can be said about the technology needed for AI success: breaking down silos, intelligent automation, or multi-database analytics.
However, an automated software architecture that facilitates seamless integration of third-party services, strategic business tools, and next-generation technologies like Artificial Intelligence makes all of it possible.
It is the foundation for a highly sophisticated digital platform that aligns with business, user, and vertical needs.
Assuming you’ve already started moving to cloud-delivered service models, you’ll also want to begin transitioning to automated architecture software to harness the full power of the cloud. It allows you to quickly and safely start scaling towards AI-powered results.
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