AI becomes an indispensable, trusted enterprise coworker in 2023

AI adoption is no longer an emerging trend, with 73% of data and analytics decision-makers building AI technologies and 74% seeing a positive impact in their organizations, according to Forrester’s Data and Analytics Survey, 2022.

As more companies succeed in implementing the fundamentals of AI practices, we are seeing the beginnings of a step-change surge of horizontal and vertical use cases that are transforming the way enterprises perform fundamental functions — from coding to content generation.

Enterprises of any size from any industry can capitalize on at least some of the opportunities offered by the implementation of AI-supported software development and visual/textual content generation, deliberate governance reporting, faster time to care in healthcare, and increased trust with users engaging transparently with virtual agents. In 2023, Forrester predicts that:

• TuringBots will write 10% of worldwide code and tests.
  
  It’s not low-code. It’s not no-code. It’s AI that writes code that Forrester called TuringBots in 2020, and it’s here. Reinforcement learning and large language models have accelerated the development, accuracy, and deployment of products that can automatically generate clean code from requirements expressed in natural language.

In 2020, TuringBots were available for software testing, and today they are available for coding as well. In 2023, we expect them to take on more aspects of the software development lifecycle. Amazon Code-Whisperer, CodeBot, GitHub Co-Pilot, Tabnine, and others are becoming elegantly embedded in developer tools, making them easy to try, use, and become part of development.

The Better Health Generation used CodeBot to generate 91% of the 180K lines of the application code for a mental health application. Development teams should start planning, experimenting, and working with TuringBots using a differentiated strategy: Optimize and refactor development with data-driven TuringBots and accelerate adoption of testing TuringBots for autonomous and smarter testing.

• 10% of Fortune 500 enterprises will generate content with AI tools.
  
  Human-produced content-creation will never be fast enough to address the need for personalized content at scale, and in the next year we expect to see at least 10% of companies invest in AI-supported digital content creation. The evolution in transformer networks and pretrained models (particularly large language models like BERT and GPT-3) are paving the way.

Leading vendors like Baidu and Huawei have already launched their digital content services powered by computer vision (CV). Startups like Synthesia and HourOne.ai are using AI to accelerate video content generation and Taichi Graphics raised $50 million for CV-powered digital content creation. Popular text-to-image tools like Dall-E mini and Stable Diffusion are enabling content-creators of all types (even tech industry analysts) to quickly generate content.

Technology leaders should evaluate the business potential of AI-powered digital content to accelerate and expand content generation, recommendation, and delivery for differentiated customer engagement faster and at scale.

• One in four tech execs will report to their board on AI governance.
  
  Mounting regulation and demand for trust in AI will drive one in four CIOs and CTOs to lead AI governance. AI governance will join cybersecurity and compliance as a board-level topic that will impact the technology differentiation and risk mitigation oversight for the firm and necessitate a designated point of contact in the C-suite.

Highly-regulated industries (financial services, healthcare) and geographies (Europe) will move first, while the US test-drives new frameworks. Board reporting will cover explainability, fairness audits of high-impact algorithmic decision-making, and environmental impacts of AI (green AI). Forrester’s data shows that 46% of data and analytics business and technology decision-makers seek out partners to implement AI critical to the business.

Accenture, BCG, Deloitte, EY, and McKinsey already offer auditing and executive training on AI governance. Future fit tech execs should embrace their new AI governance role and use the opportunity to put ethical technology strategy into practice across the organization.

• AI in retail healthcare will reduce time to care by 25%.
  
  Retail healthcare will use intelligent scheduling to chip away at the $150 billion problem of healthcare no-shows: Walgreens is partnering with Nuance to schedule COVID-19 vaccine appointments 24/7, and Minute Clinic at CVS partnered with Google to enable same-day scheduling via Google Search.

In 2023, AI will use insurance coverage, diagnosis, location, availability, and cancellation risk factors to optimize scheduling workflows. Innovative companies will use this data to fill costly gaps from last-minute cancellations — intelligent systems will reach out to waitlisted patients based on the predicted likelihood to respond. Solving this problem will reduce the 20.6 day average wait to see a physician by 25%.

Retail health will spearhead this initiative leading to seismic disruption and mounting pressure for traditional health care organizations to step up their patient experience. Traditional healthcare practices should invest in AI scheduling software to remain relevant, or they will be outmaneuvered by the competition.

• Companies will drop the human-like pretense for virtual assistants to improve trust.
  
  B2B companies are expanding their use cases for conversational AI solutions to support the full customer lifecycle, enabling buyers, customers, and employees to handle more complex information exchanges and business logic.

Currently, 65% of B2B marketers with conversation automation use AI-powered virtual assistants to engage and enable customer and employee audiences. In some scenarios, the virtual assistants automating these conversations pretend to be human, leading the customer to feel tricked. To safeguard customer trust, companies will invest in developing personas for these nonhuman team members that embrace transparency in their identity as a virtual assistant.

In 2023, companies will further experiment with AI personas as brand assets as companies seek to differentiate these conversational interactions by demonstrating respect and relevance for the customer. This transparency will contribute to a measurable increase in customer trust in the brand and the technology end-user’s trust in AI over the next two years.

Summary

In 2022, we have seen AI adoption evolve from an emerging trend to a legitimate priority for organizations. Companies across all verticals and maturity levels are finding opportunities to implement AI. This implementation is yielding positive results in terms of both, effectiveness and efficiency, and is allowing organizations to transform fundamental functions. We predict that in 2023, AI adoption within enterprises will continue to expand, and be more creative, trustworthy, and optimized.

-- Forrester Research