AI will become an indispensable, trusted company colleague in 2023 | Tech Rasta

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

As more companies succeed in implementing the basics of AI practices, we are witnessing the beginning of a phase-change of horizontal and vertical use cases that will transform the way enterprises perform basic functions – from coding to content production.

Enterprises from any industry and of any size can take advantage of some of the opportunities offered by AI-supported software development and visual/textual content generation, purposeful governance reporting, faster turnaround time in healthcare and increased trust with engaged consumers. Transparent with virtual agents. In 2023, Forrester predicts:

  • TuringBots write 10% of code and tests worldwide.
    This is not low code. This is no-code. This is the code-writing AI that Forrester calls Turingbots in 2020, and here it is. 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 are available for software testing and today they are also available for coding. 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 well-integrated developer tools that make it easy to try, use, and be a part of development.

Better Health Generation used Codebot to generate 91% of the 180K lines of application code for a mental health application. Development teams should start planning, experimenting, and working with Turingbots using a different strategy: optimize and refactor development with data-driven Turingbots, and accelerate testing Turingbots for autonomous and intelligent testing.

  • 10% of Fortune 500 enterprises produce content with AI tools.
    Human-generated content-creation is not fast enough to address the need for personalized content at scale, and we expect at least 10% of companies to invest in AI-supported digital content creation in the next year. Evolution in transformer networks and pretrained models (especially large language models such as BERT and GPT-3) are paving the way.

Leading vendors such as Baidu and Huawei have already launched their digital content services powered by computer vision (CV). Startups like Synthesia and are using AI to accelerate video content production, and Taichi Graphics has raised $50 million for CV-based digital content creation. Popular text-to-image tools like Doll-e Mini and Stable Diffusion allow all kinds of content-creators (even tech industry analysts) to quickly create content.

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

  • One in four tech executives report to their board on AI governance.
    Mounting regulation and demand for trust in AI drives one in four CIOs and CTOs to lead AI governance. AI governance incorporates cybersecurity and compliance as a board-level topic that impacts technology differentiation and risk mitigation oversight for the organization and requires a designated point of contact in the C-suite.

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

Accenture, BCG, Deloitte, EY and McKinsey already offer auditing and executive training on AI governance. Future fit tech executives should embrace their new AI governance role and seize the opportunity to implement an ethical technology strategy across the organization.

  • AI can reduce care time by 25% in retail healthcare.
    Retail Healthcare Uses Intelligent Scheduling to Overcome the $150 Billion Healthcare No-Shows Problem: Walgreens partnered with Nuance to schedule COVID-19 vaccine appointments 24/7, and Minute Clinic at CVS partnered with Google to launch same-day scheduling. Through Google search.

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

Retail health is leading this initiative, which will lead to seismic disruption and increase pressure for traditional healthcare organizations to improve their patient experience. Traditional healthcare practices must invest in AI scheduling software to stay relevant, or they will be overtaken by the competition.

  • Companies ditch the human 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 communications and business logic.

Currently, 65% of B2B marketers use AI-powered virtual assistants to engage and enable customer and employee audiences with conversational automation. In some cases, the virtual assistants that automate these conversations pretend to be human, which can trick the customer. To maintain customer trust, companies invest in developing personas for these non-human team members who embrace transparency in their identities as virtual assistants.

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

In 2022, we see 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 enables organizations to transform core functions. In 2023, we predict that AI adoption in enterprises will continue to expand and become more creative, reliable and optimized.

– Forrester Research

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