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Execs double down on AI: explore 5 AI adoption strategies for success

2024-07-17 17:31:08EY

New EY AI Pulse Survey reveals that AI investments are set to double, but many companies are failing to invest in necessary infrastructure.

In brief

  • Blend custom AI development with ready-made solutions for a balanced investment strategy.

  • Implement “responsible AI” protocols to gain trust and outpace regulatory developments.

  • Invest in top AI talent and elevate current employees’ skills for a robust, AI-fluid workforce.


Artificial intelligence (AI) is redefining the competitive business landscape, with leaders actively investing to capitalize on its transformative promise. To investigate top-tier investment trends and perceptions in AI technology adoption among corporate leaders, as well as uncovering the state of AI in the US, we commissioned a survey among 500 senior executives across a spectrum of industries. Survey findings indicate a projected nearly twofold increase in AI investments, exceeding US$10 million or more in the next year, among those who are already investing, signaling AI’s shift to a central role in corporate growth strategies.


This sentiment follows a year in which AI investments had already significantly increased in pace. Just three years ago about half of senior leaders said their organization spent less than 5% of its total budget on AI investments. In contrast, today, 88% of those same leaders spend 5% or more of their total budget on AI. It’s a number that is set to grow even higher, as half of senior leaders said they would dedicate 25% or more of their total budget toward AI investments in the coming year.

 

At the same time, those already doubling down on investments are seeing the impact. While nearly all are investing in AI, our findings indicate a divergence between companies experimenting in small ways and those making larger investments. Senior leaders whose organizations are investing in AI and whose current budget for AI investments is 5% or more of their total budget saw higher rates of positive return across dimensions surveyed, compared with those who spend less than 5%.

 

However, despite the forecast investment boom, our findings also indicate that many leaders are ignoring the foundational functions AI needs in order to thrive. Successful AI adoption demands more than just technological integration; it’s about adapting to a new paradigm whereby AI reshapes every aspect of the enterprise. From building a scalable data infrastructure to fostering a workforce fluent in emerging technologies, the research emphasizes the need for a holistic approach to AI adoption. As we stand on the cusp of an AI-driven era, the message is clear: Those who invest wisely in AI today will be the industry trailblazers of tomorrow.


This article illuminates the essential strategies executives should deploy to navigate the complexities of AI adoption as their investments increase, including five key takeaways:


Chapter 1: Leaders should adopt diversified AI investment strategies

A balanced AI investment strategy marries proprietary innovation with off-the-shelf commercial technology.


In the search for operational excellence, businesses are turning to AI as a transformative technology. Custom AI development stands out for its ability to enhance enterprise operations, delivering peak efficiency and intelligent workflow management tailored to the intricate needs of the business. Simultaneously, the allure of pre-built AI technologies lies in their ability to offer immediate implementation and a more favorable cost structure. Discerning businesses should undertake a comprehensive analysis of their operational requirements, competitive landscape and long-term goals to determine the optimal blend of in-house and off-the-shelf AI solutions. By doing so, they position themselves to leverage the full spectrum of AI benefits, establishing a strategic advantage in the rapidly evolving marketplace.

With 95% of senior leaders saying their organization is currently investing in AI, the key investment focus lies in balancing custom AI development (56%) and the acquisition of ready-made AI products (56%).

This strategy allows for tailored solutions where necessary, while also leveraging the speed and cost-efficiency of pre-built AI technologies.


Chapter 2: Prioritize ROI-driven AI deployment

Accelerate ROI by investing in AI tools that enhance operational efficiency and employee productivity.


Forward-thinking enterprises are looking to AI as a catalyst for business transformation. Strategic deployment of AI is crucial for firms aiming to strengthen their performance and realize cost efficiencies. By focusing on AI solutions that improve operational workflows and enhance employee productivity, organizations can convert traditional business models into AI-powered intelligent operations. This advancement goes beyond simple task improvement — it calls for a radical redesign of business processes to be AI-centric. By doing so, companies are not just automating; they are innovating, so that their investments in AI yield measurable financial returns and solidify their standing for the future.

About a third (34%) of senior leaders say their organization is tracking the impact of AI initiatives fully and at scale. The survey shows that among organizations investing in AI, these investments are delivering positive returns, especially in areas like operational efficiencies (77%), employee productivity (74%) and customer satisfaction (72%).


Chapter 3:Align your business and AI maturity roadmap

Advance AI maturity by syncing AI projects with business objectives and upgrading data frameworks.


Capturing the full potential of AI requires more than just technological investment; it demands a strategic alignment that integrates AI initiatives with the core objectives of the business. A robust and well-structured data infrastructure is critical, as it underpins intelligent operations and aligns with the company’s strategic pursuits. This alignment paves the way for enhanced decision-making capabilities and a fertile environment for innovation. By achieving strategic AI maturity, organizations can transition into “superfluid” entities, characterized by their seamless decision-making processes and a relentless drive for innovation. In this way, a strong data foundation not only supports AI, but also propels businesses toward their goals with unprecedented efficiency and insight.

A superfluid enterprise is a highly agile and adaptable organization, leveraging digital innovation to swiftly respond to market shifts, improve processes and drive continuous growth, facilitating sustained competitive advantage.

  • About 34% of senior executives report that their organization is aligning AI strategy with business objectives fully and at scale.

  • Similarly, only 36% of senior leaders report that their organization is investing in data infrastructure (i.e. quality, accessibility and governance of data) fully and at scale.

  • 35% of senior leaders report that their organization is creating a roadmap for AI implementation fully and at scale.


Chapter 4: Invest in responsible AI as a competitive edge

Adopt ethical AI standards to foster trust and pre-empt regulatory challenges.


The surge in executive interest in responsible AI marks a pivotal shift in business strategy, placing ethical considerations at the forefront of AI adoption. To navigate this new terrain, companies should consider investing in comprehensive AI governance frameworks and strategies for mitigating bias, thereby safeguarding that their AI systems uphold fairness and transparency. Firms that excel in responsible AI not only distinguish themselves in a competitive marketplace, but also fortify themselves against future regulatory issues. In addition, ethical AI practices are a linchpin in the creation of a superfluid enterprise, where stakeholder trust is strengthened, compliance is effortlessly maintained and operational friction is reduced, all of which propels innovation. Pioneers in this area are setting a new industry standard, providing services that are both transparent and equitable, and charting the course for the future of AI-powered businesses.

There is clear interest in responsible AI, but leaders are not taking the necessary steps to realize this interest.

  • 53% of senior leaders whose organization is investing in AI reporting increased organizational interest in responsible AI over the past year.

  • 34% of senior leaders say their organization is building an AI governance framework fully and at scale.

  • 32% of senior leaders say their organization is addressing bias in AI models fully and at scale.


Chapter 5: Embrace talent development as a value driver

Concentrate on acquiring AI specialists and enhancing staff competencies to build an adept AI-fluent workforce.

The scarcity of AI skills in the job market is a clarion call for businesses to invest in extensive employee upskilling and re-skilling programs. By cultivating AI skills within their existing workforce, companies can not only expedite the adoption of AI technologies but also secure a vital competitive advantage. Developing an internal pipeline of AI talent is essential for fostering a workforce that is not just proficient but superfluid — adaptable, innovative and fully equipped to leverage AI for maximum impact. Moreover, by placing a premium on attracting and nurturing AI-savvy employees, organizations can establish that their operations are driven by professionals that can unlock the full spectrum of AI's capabilities, positioning the business at the forefront of technological advancement.

  • There is clearly a gap and talent is hard to find, but only 40% of senior leaders are encouraging employees to embrace AI fully and at scale. Additionally, only 37% of senior leaders say their organization is training/upskilling employees on AI fully and at scale.

  • With 83% of senior leaders prioritizing attracting workers who are knowledgeable of AI, businesses must recognize the importance of building an AI-competent workforce. The difficulty in finding employees with the AI skill set needed for their organization 78% underscores the need for comprehensive upskilling programs.


Conclusion


1. Invest in AI to stay competitive and drive innovation

The burgeoning influence of AI on the business landscape is undeniable, with our survey of 500 senior executives revealing a significant uptick in AI investments. This is not merely a trend but a strategic imperative; companies that do not actively engage with AI risk being left behind in a market that increasingly rewards innovation and agility. As we have seen, the future belongs to those who recognize AI's potential to redefine every facet of their operations — from process improvement to decision-making — and invest accordingly.


2. Balance custom and ready-made AI solutions

A diversified AI investment strategy is paramount. Companies must balance the allure of ready-made AI technology solutions with the bespoke advantages of custom development to create a hybrid model that aligns with their unique business needs. This approach enables organizations to harness AI's full potential while maintaining flexibility in a dynamic market. In addition, the focus must be on ROI-driven AI deployment. Investments in AI should not be made for the sake of technology alone; they must be tied to clear, measurable business outcomes. Organizations that prioritize AI applications with direct impact on operational efficiency and productivity will not only see immediate benefits but also set the stage for long-term financial success.


3. Lead with Responsible AI to gain trust and a market edge

It's important to note that championing responsible AI is not just an ethical mandate but a competitive differentiator. As AI becomes more widespread, companies that lead with transparency, fairness, and governance will build trust and resilience, positioning themselves favorably in the eyes of consumers and regulators alike.


4. Ensure your AI initiatives align with strategic business goals

Aligning business and AI maturity roadmaps is crucial. Organizations must verify that their data infrastructure and AI initiatives are in lockstep with their strategic goals. This synergy will enable them to make smarter decisions faster and foster an environment ripe for continuous innovation.


5. Prioritize talent development to harness the full power of AI

Talent development is a critical value driver in the AI equation. The scarcity of AI competencies necessitates a proactive approach to upskilling and attracting top talent. Companies that build a robust internal pipeline of AI skills will not only accelerate technology integration but also secure a lasting competitive edge.


Summary

After more than a year of hype around generative AI’s potential, business leaders report they are already seeing a return on their AI investments and plan to increasingly become more bullish. However, significant risks still stand in the path to enterprise-wide AI adoption, including data infrastructure, ethical frameworks, and talent acquisition. The transformative journey into an AI-driven future demands a holistic and strategic approach. Those who act now will emerge as the trailblazers, setting the pace for an intelligent, superfluid enterprise that is both innovative and sustainable

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