[Reading level: C1 – Advanced]
Most growth models and strategies — such as the Ansoff Matrix and McKinsey’s 7S Framework — are focused on external expansion: Grow by launching new products, by entering new markets, and by doing both at once. Yet growth can also come from within, by developing internal capability.
AI offers many ways to enhance overall internal capability and skills. AI can be used to infer skills from employee profiles and their activity. AI can be used to classify learning content and make it more applicable and accessible for the whole workforce, as well as making learning more personalized to each individual. AI can be used to summarize, recommend, and augment learning content. Gen AI, in particular, can be used by the world’s billion knowledge workers to boost performance, right in the flow of work.
Let’s focus on the last of these capability-enhancing measures: Using AI to help us carry out tasks better and faster, and how this can fuel new growth in your organization.
Research Shows that AI-Fueled Capability Growth Is Very Likely
How do we know that AI is going to boost growth? By how much? What’s the gain for your organization? Or your department? Or your team? And what might the productivity gain be for you, personally?
These questions are not easy to answer but we can have a go at it. Studies have been devised to quantify all manner of capabilities, such as the effectiveness of gen AI advertisements, the ability of gen AI to provide moral guidance, and its ability to guess what others are thinking.
In your business, you may well be able to take a more down-to-earth approach. Perhaps you can measure a change in productivity in one business area (say, the speed of conducting research for sales calls) and infer it in other areas (say, how much faster research might be conducted for digital marketing campaigns). Don’t let the great be the enemy of the good. The perfect measure of capability-driven productivity gain doesn’t exist, so choose a measure that is directionally useful and undertake to refine it further down the line.
One influential study from 2023 concluded that gen AI can get knowledge work done 25% faster and 40% better. And that project was conducted using models which are no longer cutting-edge (or frontier, to use AI parlance), so an equivalent study now might yield even greater upsides. Even if these figures are overstated and the uplifts for quality and speed were both, say, 10%, we’d still see a compounded 21% productivity jump.
The gains from utilizing gen AI seem, then, to be considerable.
Let’s suppose, then, that you have a productivity gain statistic that you can rally people behind and you have a green light to trial gen AI. How will you get people to join in?
We’ve Been Here Before
There are many precedents for the rapid, large-scale adoption of technology to accelerate productivity and growth. Personal computers, spreadsheets, the internet, email, and smartphones were all unknown quantities once, encountering resistance and cynicism. But now they’re ubiquitous.
The rise of the internet may be the most relevant bellwether for gen AI. The internet was based on a vast network of IT infrastructure and previous technological advances. Its uses and impact were not clear to most people, though there was the rare clairvoyant. But after a while, its value was felt by individuals and businesses alike. It gave rise to perceived and actual societal imbalances (unequal access to high-speed infrastructure, filter bubbles, data exploitation), such was its power and influence.
All of these are also true of gen AI. And while the internet has been a major milestone in human history, and its adoption has been phenomenal (from a few thousand people in the 80s to ~20 million in 1994, to 5.35 billion today), gen AI has enjoyed much faster adoption, indeed the fastest-ever user base growth.
Several tech companies battled it out at the dawn of the internet. Netscape, AOL, and Yahoo were or became significant players, but they weren’t the world’s biggest companies back then (and are much less so now). But today, we already have every single one of the world’s largest companies pushing the AI agenda hard. Microsoft is leading the charge, rolling out CoPilot to companies of all sizes. The four next-biggest companies (Nvidia, Apple, Alphabet, Amazon) are also famously and infamously active here.
So, rapid worldwide adoption can be done, has been done, and is happening even more quickly today, in the case of gen AI.
What can you do — in your business, team, and for yourself — to participate in and accelerate gen AI utilization and its attendant benefits?
How Corporations Can Tap Into AI-Powered Growth
Corporations are simultaneously under pressure to respond quickly to the promise of gen AI as well as to avoid risk to IP or reputation. Here are a few ways for firms to be up and running fast, without falling over.
Celebrate curiosity and experimentation.
Encourage experiments in safe domains and share the results widely, even (especially!) when they do not yield the expected results that had been envisaged. If you’re looking for a safe, useful project, consider this demand-risk 2×2 framework to help you find one. Be clear with staff about protocols regarding sensitive company data, to prevent IP and PR disasters. Make that encouragement concrete by proposing a set amount of time per week for employees to learn about and experiment with gen AI (for self-directed learning, an hour per week is a good start). There is a productivity price to pay for not being curious.
Start with pilot programs.
Small, controlled pilot projects can enable teams to gain familiarity with gen AI, understand its implications, build confidence, and learn from external experts. These pilots will serve as a testing ground and launch pad for larger-scale implementations. They are an investment.
Create gen AI champions.
Passionate, knowledgeable enthusiasts can accelerate gen AI adoption by advocating for its benefits, identifying use cases, providing peer support, and sharing the good practices that emerge. These people are gold. You may want to officially recognize, financially incentivize, and provide a budget for such AI advocates. Just be sure to find people who are actually making a difference — not all, but many AI communities of interest, gen AI task forces, and volunteer groups lack teeth and soon fizzle out.
Measure and monitor success.
As we’ve discussed, this is easier said than done. But at the very least, case studies can be compiled and shared to inspire and educate. It may also be possible for some experiments to calibrate against existing studies such as the aforementioned study which concluded that gen AI can get knowledge work done 25% faster and 40% better. That’s a tangible, ready-made target to try to beat.
How teams can tap into ai-powered growth
Whether or not you’re the leader of your team, this is a case where you can lead by example. Come to team meetings with a story of how you’ve used gen AI. You’ll inspire other, fellow enthusiasts and demonstrate to the as–yet uninitiated that these efforts are valuable and rewarding.
Use ChatGPT, live, in a team meeting. Ask it a question that has stumped you all. Invite it to participate alongside you in a brainstorming session. Get it to generate a summary of your team meeting. Nothing convinces non-believers more effectively than relevant, real-time use.
How Individuals Can Tap Into AI-Powered Growth
Like all technology, you won’t achieve sustained growth with gen AI unless it’s truly needed. Find a use case in your daily work. These 100 use cases may help get you started, and the following are especially useful in a business context:
- Generating ideas
- Adjusting the tone of emails
- Evaluating copy
- Generating appraisals
- Being a safe space to ask questions
- Writing realistic web copy
Trust is one of the biggest barriers to gen AI adoption. Half of people still don’t trust it (and trust is lower among women, low-income, and older age groups). The most effective means of establishing trust is for people to find a use case that they care about and which works for them.
If you’re not permitted to use gen AI at work, stay on track, obviously. But don’t let that make you fall off the gen AI superhighway. While some cunning employees are using gen AI covertly, you can also experiment with gen AI outside of the confines of your work life.
Embracing gen AI can drive internal growth by enhancing organizational capability. This kind of growth may take a little longer to manifest in revenues and profit. But its impact will be longer-lasting, since it’s for your people, your organization’s heartbeat. Mechanisms for measuring this growth are still evolving, but the early signs are that double–digit growth via gen AI is eminently possible.
Source: https://hbr.org/2024/07/how-ai-can-change-the-way-your-company-gets-work-done?ab=HP-hero-featured-text-1
WORD BANK:
internal /ɪnˈtɜː.nəl/ [B2] (a): nội bộ, bên trong
capability /ˌkeɪ.pəˈbɪl.ə.ti/ [C1] (n): năng lực
infer /ɪnˈfɜːr/ [C2] (v): suy luận
profile /ˈprəʊ.faɪl/ [B2] (n): hồ sơ
classify /ˈklæs.ɪ.faɪ/ [C1] (v): phân loại
applicable /əˈplɪk.ə.bəl/ (a): áp dụng, có thể áp dụng
accessible /əkˈses.ə.bəl/ [B2] (a): tiếp cận
augment /ɔːɡˈment/ (n): tăng thêm
performance /pəˈfɔː.məns/ [B2] (n) hiệu suất
fuel /ˈfjuː.əl/ [B2] (v): thúc đẩy, làm tăng
boost /buːst/ [B2] (v): thúc đẩy
have to go at sth (phr.): thử làm một việc gì đó
devise /dɪˈvaɪz/ [C2] (v): thực hiện, lập ra
quantify /ˈkwɒn.tɪ.faɪ/ (v) đo lường, định lượng
moral /ˈmɒr.əl/ [B2] (a): đạo đức
down-to-earth /ˌdaʊn.tuːˈɜːθ/ [C1] (a): thực tế
undertake /ˌʌndəˈteɪk/ [C2] (v): cam kết
refine /rɪˈfaɪn/ [C1] (v): cải tiến
down the line (idiom): trong tương lai
cutting-edge /ˌkʌt.ɪŋˈedʒ/ [C1] (a) tiên tiến
frontier /ˈfrʌn.tɪər/ [C2] (n): tối tân
parlance /ˈpɑː.ləns/ (n): cách nói
equivalent /ɪˈkwɪv.əl.ənt/ [C1] (a): tương đương
yield /jiːld/ [C2] (v): mang lại, cung cấp, đưa ra (kết quả)
uplift /ˈʌp.lɪft/ (n): cải thiện
overstated /ˌəʊ.vəˈsteɪt/ (v): phóng đại
compound /ˈkɒm.paʊnd/ (v): gộp lại
utilize /ˈjuː.təl.aɪz/ (v): sử dụng
considerable /kənˈsɪd.ər.ə.bəl/ [B2] (a): lớn, đáng kể
statistic /stəˈtɪs.tɪk/ [B2] (n): thống kê
rally /ˈræl.i/ (v): tập hợp
give/have a green the green light to do sth (idiom): cho phép làm gì
precedent /ˈpres.ɪ.dənt/ [C2] (n): tiền lệ
accelerate /əkˈsel.ə.reɪt/ [C2] (v): thúc đẩy
resistance /rɪˈzɪs.təns/ [C2] (n): sự phản kháng
cynicism /ˈsɪn.ɪ.sɪ.zəm/ (n): sự hoài nghi
ubiquitous /juːˈbɪk.wə.t̬əs/ có mặt ở khắp mọi nơi
bellwether /ˈbelˌweð.ər/ (n): dấu hiệu
clairvoyant /ˌkleəˈvɔɪ.ənt/ (a): khả nhận thấy trước được(tương lai)
perceive /pəˈsiːv/ [C1] (v): cảm nhận
give rise to [C2] (idiom): gây ra
unequal /ʌnˈiː.kwəl/ (a): chênh lệch
filter bubble (n): bóng bóng bộ lọc
phenomenal /fəˈnɒm.ɪ.nəl/ [C2] (a): mang tính hiện tượng
adoption /əˈdɒp.ʃən/ [B2] (n): sự áp dụng, ứng dụng (những thứ mới)
battle it out: cạnh tranh khốc liệt
the drawn of sth [C1] (phr.): bắt đầu một thứ gì đó mới
agenda /əˈdʒen.də/ [C1] (n): chương trình nghị sự
lead the charge: dẫn đầu cuộc đua
roll out (phr.v): triển khai
infamously /ˈɪn.fə.məs.li/ (adv): tai tiếng
attendant /əˈten.dənt/ (a): đi kèm, kèm theo
Tap in to /tæp/ (phr.v): khai thác
simultaneously /ˌsɪm.əlˈteɪ.ni.əs.li/ [B2] (adv): đồng thời
promise /ˈprɒm.ɪs/ (n): tiềm năng, lợi ích có thể mang lại
Intellectual Property(IP) (n): Tài sản trí tuệ
curiosity /ˌkjʊə.riˈɒs.ə.ti/ [B2] (n): sự tò mò
experimentation /ɪkˌsper.ɪ.menˈteɪ.ʃən/ (n): sự thử nghiệm
domain /doʊˈmeɪn/ lĩnh vực, vùng
envisage /ɪnˈvɪz.ɪdʒ/ [C1]: hình dung
protocol /ˈprəʊ.tə.kɒl/ (n) quy đinh, quy tắc
self-directed learning: tự học
pilot /ˈpaɪ.lət/ (a): thí nghiệm, thí điểm
implication /ˌɪm.plɪˈkeɪ.ʃən/ (n): hàm ý
launch pad (n): bệ phóng
implementation /ˌɪm.plɪ.menˈteɪ.ʃən/ [C2] (n): sự triển khai
passionate /ˈpæʃ.ən.ət/ [B2] (a): nhiệt huyết
knowledgeable /ˈnɒl.ɪ.dʒə.bəl/ [C1] (a): có kiến thức
advocate /ˈæd.və.keɪt/ [C2] (v): ủng hộ
incentivize /ɪnˈsen.tɪ.vaɪz/ (v): khuyến khích
teeth /tiːθ/ (n): sức mạnh
fizzle out /ˈfɪz.əl/ (phr.v): thất bại
compile /kəmˈpaɪl/ [C1] (v): biên soạn
calibrate /ˈkæl.ɪ.breɪt/ (v): hiệu chỉnh
aforementioned /əˈfɔːˌmen.ʃənd/ (a): như đã được được đề cập ở trên
tangible /ˈtæn.dʒə.bəl/ [B2] (adj): cụ thể, rõ ràng
ready-made (adj): sẵn có
demonstrate /ˈdem.ən.streɪt/ [B2] (v): chứng minh
uninitiated /ˌʌn.ɪˈnɪʃ.i.eɪ.tɪd/ (adj): chưa từng, không quen
as-yet: cho đến nay
rewarding /rɪˈwɔː.dɪŋ/ (adj): bổ ích
stump /stʌmp/ (v): hỏi khó
appraisal /əˈpreɪ.zəl/ sự đánh giá
barrier /ˈbær.i.ər/ [B2] (n): rào cản
cunning /ˈkʌn.ɪŋ/ [C2] (adj): xảo quyệt
covertly /ˈkəʊ.vɜːt.li/ (adv): một cách lén lút, một cách bí mật
confine /kənˈfaɪn/ [C2] (v): phạm vi
drive growth (phr.v): thúc đẩy tăng trưởng
heartbeat /ˈhɑːt.biːt/ (n): nhịp đập, người/ thứ quan trọng(trong một nhóm)
manifest /ˈmæn.ɪ.fest/ (v): biểu thị, biểu hiện
double-digit /ˌdʌb.əlˈdɪdʒɪt/ (adj): hai con số (từ 10 đến 99)
eminently /ˈem.ɪ.nənt.li/ (adv): cực kỳ
mechanism /ˈmek.ə.nɪ.zəm/ [C1] (n): cơ chế
evolve /ɪˈvɒlv/ [C1] (v): phát triển
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